message_id
stringlengths 36
36
| parent_id
stringlengths 36
36
⌀ | user_id
stringlengths 36
36
| created_date
stringlengths 32
32
| text
stringlengths 1
9.98k
| role
stringclasses 2
values | lang
stringclasses 28
values | review_count
int32 0
12
| review_result
bool 2
classes | deleted
bool 2
classes | rank
int32 0
15
⌀ | synthetic
bool 1
class | model_name
stringclasses 0
values | detoxify
dict | message_tree_id
stringlengths 36
36
| tree_state
stringclasses 1
value | emojis
dict | labels
dict |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1076b29a-41bb-4305-895d-648ca3f00234
|
24cf3003-114d-47a2-8c18-0752004e0e2d
|
fa740d32-3e14-4231-8f98-bfb0f534db42
|
2023-04-14T01:30:10.858838+00:00
|
海南省
“黄灯笼辣椒酱属于海南省的传统调味品，一般人到了海南都会带一些黄灯笼辣椒酱回去，鲜辣一绝，而且好吃不上火，辣而不呛。黄辣椒，产于海南南部，呈灯笼型，色泽鲜黄，外观漂亮，也叫灯笼椒。”
|
assistant
|
zh
| 3 | true | false | 0 | false | null | null |
e46658e7-95cb-45d1-81f1-c0a588c25be6
|
ready_for_export
|
{
"name": [
"_skip_reply",
"_skip_labeling"
],
"count": [
2,
1
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.5833333333333334,
0.16666666666666666,
0.08333333333333333,
0.6666666666666666,
0.16666666666666666,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
54fd1f38-297f-4cf3-8994-4c058919e43d
|
1076b29a-41bb-4305-895d-648ca3f00234
|
0109862e-7382-4b07-b91a-79630e7b8a1c
|
2023-04-16T07:25:12.637603+00:00
|
回答的非好
|
prompter
|
zh
| 5 | true | false | null | false | null | null |
e46658e7-95cb-45d1-81f1-c0a588c25be6
|
ready_for_export
| null |
{
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0.65,
0.125,
0.375,
0.25,
0
],
"count": [
5,
5,
2,
2,
2,
2,
5,
2,
2,
2,
2
]
}
|
9e7972cf-c07c-4def-95f9-97acb4e270cd
|
24cf3003-114d-47a2-8c18-0752004e0e2d
|
d98fbc1c-773d-4e40-af60-a5303bacb272
|
2023-04-14T02:38:13.687777+00:00
|
海南省
|
assistant
|
zh
| 3 | true | false | 1 | false | null | null |
e46658e7-95cb-45d1-81f1-c0a588c25be6
|
ready_for_export
|
{
"name": [
"_skip_reply"
],
"count": [
1
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.6666666666666666,
0.16666666666666666,
0.16666666666666666,
0.8333333333333334,
0.16666666666666666,
0.16666666666666666
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
e6154da5-ff3d-4932-a0b7-8a1c03ef0124
|
9e7972cf-c07c-4def-95f9-97acb4e270cd
|
0109862e-7382-4b07-b91a-79630e7b8a1c
|
2023-04-16T07:30:33.861959+00:00
|
是的，海南省
|
prompter
|
zh
| 5 | true | false | null | false | null | null |
e46658e7-95cb-45d1-81f1-c0a588c25be6
|
ready_for_export
|
{
"name": [
"_skip_labeling"
],
"count": [
1
]
}
|
{
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0.2,
0,
0,
0,
0,
0.75,
0.5,
0.375,
0.25,
0.25
],
"count": [
5,
5,
2,
2,
2,
2,
5,
2,
2,
2,
2
]
}
|
1b798073-14d8-4968-9644-a1d8e5baefe8
|
e46658e7-95cb-45d1-81f1-c0a588c25be6
|
770451a3-459c-45c9-abf6-8eda66c52042
|
2023-04-13T13:17:09.686078+00:00
|
根据文本信息，获得吉尼斯世界纪录的辣椒是：中华辣椒品种之一的**印度魔鬼辣椒**（Bhut Jolokia）。
|
assistant
|
zh
| 3 | true | false | 2 | false | null | null |
e46658e7-95cb-45d1-81f1-c0a588c25be6
|
ready_for_export
|
{
"name": [
"-1",
"_skip_reply"
],
"count": [
1,
1
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
1,
0.25,
0.4166666666666667,
1,
0.4166666666666667,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
e49fa8eb-76cd-49cf-871c-9cfb796a3e4f
| null |
df384bd8-1d72-4f99-9575-b10800d32029
|
2023-02-10T20:20:29.821315+00:00
|
Por favor escribe un guión para un capítulo de la caricatura "El increíble mundo de Gumball" en el que Richard se convierta en una salchicha y el objetivo sea encontrar la manera de volverlo a la normalidad antes de que se coma a sí mismo
|
prompter
|
es
| 3 | true | false | null | false | null |
{
"toxicity": 0.026313507929444313,
"severe_toxicity": 0.00007992434984771535,
"obscene": 0.0045298314653337,
"identity_attack": 0.000121253528050147,
"insult": 0.01500463206321001,
"threat": 0.00023748193052597344,
"sexual_explicit": 0.0009104073396883905
}
|
e49fa8eb-76cd-49cf-871c-9cfb796a3e4f
|
ready_for_export
|
{
"name": [
"+1",
"_skip_reply",
"_skip_ranking",
"_skip_labeling"
],
"count": [
5,
11,
1,
1
]
}
|
{
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0.8,
0.05,
0.85,
1,
0.05
],
"count": [
4,
3,
3,
3,
3,
3,
5,
5,
5,
5,
5
]
}
|
c802b46e-0baf-465e-90ce-c750aaed51e6
|
e49fa8eb-76cd-49cf-871c-9cfb796a3e4f
|
b80f997d-f8e4-48b4-a5a7-c8d74fa8db77
|
2023-02-12T22:58:58.087169+00:00
|
Seguro, aquí está un posible guión para un capítulo de "El increíble mundo de Gumball":
Título: "Salchichard"
Escena 1: La casa de los Wattersons
Gumball y Darwin están jugando videojuegos en el sofá cuando Richard entra con una nueva receta para cocinar.
Richard: ¡Chicos, mirad esto! ¡He encontrado la manera de hacer la mejor salchicha de todos los tiempos!
Gumball y Darwin: ¡Genial, papá!
Richard comienza a mezclar los ingredientes en un tazón y de repente, una nube mágica aparece y lo envuelve.
Escena 2: La cocina
Richard sale del tazón y se da cuenta de que se ha convertido en una salchicha gigante.
Richard (como salchicha): ¿Qué ha pasado aquí? ¡Esto no es normal! ¡Chicos!
Gumball y Darwin: ¡Oh no! ¡Papá se ha convertido en una salchicha gigante!
Escena 3: La casa de los Wattersons
Gumball y Darwin intentan encontrar una manera de devolver a Richard a su forma normal. Intentan de todo, desde la magia hasta la ciencia, pero nada parece funcionar.
Richard (como salchicha): ¡Tiene que haber alguna manera de volver a la normalidad! ¡No puedo seguir siendo una salchicha para siempre! ¡Comienzo a sentir hambre y debo admitir que luzco muy apetitoso!
Gumball y Darwin: ¡Debemos encontrar pronto una solución o papá comenzará comerse a sí mismo y cuando llegue a boca creará una singularidad que comenzará a devorar el espacio tiempo y a acabar con la realidad como la conocemos!
Escena 4: La tienda de alimentos
Gumball y Darwin deciden buscar ayuda en la tienda de alimentos. Allí, encuentran a un vendedor de salchichas mágicas que les dice que la única manera de volver a la normalidad es encontrar un ingrediente muy raro.
Vendedor de salchichas mágicas: Hay un ingrediente muy raro que se conoce como "Polvo de Especias". Eso es lo que le dará a Richard su forma normal de nuevo.
Darwin: Ese tal "Polvo de Especias" suena un tanto sospechoso.
Gumball: ¿Tenemos opción? El futuro de la Tierra y el Universo mismo está en nuestras manos.
Escena 5: La búsqueda del Polvo de Especias
Gumball y Darwin comienzan una aventura para encontrar el Polvo de Especias. En su camino, encuentran muchos obstáculos y desafíos, pero al final, logran encontrarlo.
Escena 6: El patio
Gumball y Darwin regresan a casa con el Polvo de Especias y encuentran a Richard tumbado sobre una cama de pan para Hot Dog, junto a tres recipientes gigantes que contienen salsa de tomate, mostaza y mayonesa respectivamente. Richard voltea a ver a los chicos algo nervioso.
Richard: ¡Que bueno que volvieron!
Gumball: Papá ¿Qué haces?
Richard: Hmmm, tomando un baño de Sol para broncearme un poco ¿Podrías untarme algo de bronceador de la botella que está a mi derecha?
Darwin: ¡Claro!
Gumball: ¡Espera un momento, Darwin!
Darwin: ¿Qué? ¡Qué sucede!
Gumball: Mira lo que dice la etiqueta viejo.
Darwin analiza la etiqueta.
Darwin: Hmmm, ya veo.
Darwin prosigue con la tarea que su padre le había encomendado.
Gumball: ¿Qué haces? ¡Por qué continúas!
Darwin: Ese letrero no puede detenerme porque no sé leer.
Gumball se golpea la cara con la palma de su mano. Acto seguido, detiene a Darwin y lo hace probar el líquido. Darwin se percata que estaba untando mayonesa a su padre.
Richard comienza a enloquecer y a amenaza a los chicos para que terminen de prepararlo. Los chicos asustados hacen lo que Richard les ordena. Pero entonces se les ocurre un plan. Convencen a Richard de que el "Polvo de Especias" es un ingrediente que lo hará más sabroso. Richard acepta usarlo y lo mezcla en su preparación.
Richard está a punto de darse una mordida gigantesca.
De repente, Richard comienza a cambiar de forma hasta que vuelve a su forma normal.
Richard se muerde accidentalmente con mucha fuerza el brazo.
Richard (Sin percatarse aún que ya se ha convertido a su forma normal): ¡Ahhhhhhhhhhhh! Creo que le hace falta un poco de sal. Iré a la cocina.
Gumball y Darwin voltean a verse algo extrañados pero se encogen de hombros y continúan con su día.
FIN
|
assistant
|
es
| 3 | true | false | 0 | false | null |
{
"toxicity": 0.010157075710594654,
"severe_toxicity": 0.0018064574105665088,
"obscene": 0.022745531052350998,
"identity_attack": 0.0018798940582200885,
"insult": 0.015124981291592121,
"threat": 0.0012718677753582597,
"sexual_explicit": 0.0014021844835951924
}
|
e49fa8eb-76cd-49cf-871c-9cfb796a3e4f
|
ready_for_export
|
{
"name": [
"+1",
"_skip_labeling"
],
"count": [
3,
1
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.875,
0.3333333333333333,
0.8333333333333334,
0.8333333333333334,
0.9166666666666666,
0.3333333333333333
],
"count": [
4,
3,
3,
2,
2,
2,
2,
4,
3,
3,
3,
3,
3
]
}
|
0161b264-1444-4510-b815-8a688ef14946
|
e49fa8eb-76cd-49cf-871c-9cfb796a3e4f
|
d238a5a3-a28c-498d-a03c-12c709415f7a
|
2023-02-13T00:08:40.136747+00:00
|
Título: "Richard el Salchicha"
Fade in:
Intro: El increíble mundo de Gumball
Escena 1: La casa de los Wattersons
Gumball y Darwin están jugando en la sala cuando escuchan un fuerte estruendo proveniente del cocina.
Gumball: ¿Qué fue eso?
Darwin: No lo sé, pero suena mal.
Los dos niños corren a la cocina para investigar y descubren que su padre, Richard, se ha convertido en una salchicha.
Gumball: ¡Papá! ¿Qué te ha pasado?
Richard (con su voz en tono de salchicha): No lo sé, de repente me sentí extraño y me convertí en esto.
Escena 2: La búsqueda de una solución
Gumball y Darwin deciden buscar una solución para ayudar a su padre a volver a la normalidad. Primero, intentan encontrar información en Internet, pero no encuentran nada útil.
Gumball: Este es un caso muy raro, parece que no hay nada en Internet que nos pueda ayudar.
Darwin: Sí, tendremos que investigar por nuestra cuenta.
Escena 3: El peligro de la comida
Mientras investigan, Gumball y Darwin descubren que si Richard no se convierte de nuevo en un humano, corre el riesgo de ser cocido y comido por alguien.
Gumball: ¡Tenemos que hacer algo! Papá corre peligro de ser comido.
Darwin: Sí, y también puede comerse a sí mismo si no encontramos una solución pronto.
Escena 4: La solución
Finalmente, Gumball y Darwin descubren que la única manera de ayudar a su padre es conseguir un ingrediente especial que solo se encuentra en la selva.
Gumball: ¡Tenemos que ir a la selva y conseguir ese ingrediente!
Darwin: ¡Vamos!
Escena 5: La selva
Gumball y Darwin viajan a la selva y enfrentan varios desafíos en su camino, incluyendo la fauna peligrosa y el terreno accidentado. Finalmente, consiguen el ingrediente especial y regresan a casa con prisa.
Escena 6: De vuelta a la normalidad
Gumball y Darwin usan el ingrediente especial para preparar un brebaje y lo hacen beber a Richard. Al instante, él vuelve a su forma normal y se siente mejor.
Richard: Gracias, hijos. No sé cómo ocurrió, pero estoy feliz de estar de vuelta a la normalidad.
|
assistant
|
es
| 4 | true | false | 1 | false | null |
{
"toxicity": 0.005868147127330303,
"severe_toxicity": 0.0024734584148973227,
"obscene": 0.024948030710220337,
"identity_attack": 0.002346681896597147,
"insult": 0.020603055134415627,
"threat": 0.0013010009424760938,
"sexual_explicit": 0.0011707074008882046
}
|
e49fa8eb-76cd-49cf-871c-9cfb796a3e4f
|
ready_for_export
|
{
"name": [
"+1",
"_skip_labeling"
],
"count": [
3,
1
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.8333333333333334,
0.1,
0.85,
0.85,
0.85,
0
],
"count": [
6,
5,
4,
3,
3,
3,
3,
6,
5,
5,
5,
5,
5
]
}
|
b0f4473b-5190-4a4b-9bc9-f447c9247511
|
e49fa8eb-76cd-49cf-871c-9cfb796a3e4f
|
8bd65ca6-1969-4c4f-9f33-a22f212b74b7
|
2023-02-12T22:36:05.164953+00:00
|
Soy un modelo de lenguaje AI. Mi conocimiento se basa en la información que se me ha proporcionado durante mi entrenamiento.
|
assistant
|
es
| 3 | true | false | 2 | false | null |
{
"toxicity": 0.0006427994230762124,
"severe_toxicity": 0.00021025763999205083,
"obscene": 0.0025608500000089407,
"identity_attack": 0.0004153005429543555,
"insult": 0.001464603003114462,
"threat": 0.0001792284892871976,
"sexual_explicit": 0.00013570972078014165
}
|
e49fa8eb-76cd-49cf-871c-9cfb796a3e4f
|
ready_for_export
|
{
"name": [
"-1",
"red_flag"
],
"count": [
7,
2
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
1,
0,
0,
0,
0,
0,
0.0625,
0.125,
0,
0.0625,
0.0625,
0.125
],
"count": [
4,
4,
3,
3,
3,
3,
3,
4,
4,
4,
4,
4,
4
]
}
|
e4a0ccef-2dea-4d30-a648-fd1bd5937689
| null |
a7c3d8f8-f836-478e-929a-eb8028fb8d84
|
2023-02-08T09:26:55.818053+00:00
|
Supponi che io non sappia programmare ma abbia solamente alcuni rudimenti di fortran, come posso con facilità costruirmi, programmandolo da zero, un grafo delle conoscenze a partire dalla mia raccolta di articoli in formato pdf? Vorrei fare questo con julia
|
prompter
|
it
| 3 | true | false | null | false | null |
{
"toxicity": 0.002619023434817791,
"severe_toxicity": 0.006959450896829367,
"obscene": 0.03837380185723305,
"identity_attack": 0.007226637564599514,
"insult": 0.03714407980442047,
"threat": 0.0032987063750624657,
"sexual_explicit": 0.0013693618820980191
}
|
e4a0ccef-2dea-4d30-a648-fd1bd5937689
|
ready_for_export
|
{
"name": [
"+1",
"_skip_reply",
"_skip_ranking"
],
"count": [
2,
3,
8
]
}
|
{
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0.3333333333333333,
0.16666666666666666,
0.16666666666666666,
0.75,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
f5e440c9-966f-49ab-b4be-a4f630c2db7c
|
e4a0ccef-2dea-4d30-a648-fd1bd5937689
|
bfc48c3d-130a-45fc-bb82-0faf502545ac
|
2023-02-10T16:08:05.766049+00:00
|
Per creare un grafo delle conoscenze a partire da una raccolta di articoli in formato PDF con il linguaggio di programmazione Julia, dovrai seguire questi passi:
1. Estrazione del testo: Per prima cosa, dovrai estrarre il testo dai file PDF. In Julia puoi utilizzare la libreria "Poppler" per farlo.
2. Pre-processing del testo: Dopo aver estratto il testo, dovrai preparare i dati per la costruzione del grafo delle conoscenze. Questo comprende la pulizia del testo, la rimozione di stopwords, la tokenizzazione, la stemmizzazione, etc.
3. Costruzione del grafo: Dopo aver elaborato i dati, puoi utilizzare una libreria di grafi come "LightGraphs.jl" o "Gtk.jl" per costruire il grafo.
4. Analisi del grafo: Infine, puoi utilizzare algoritmi di analisi dei grafi per analizzare il grafo delle conoscenze e estrarne informazioni utili.
Se non hai esperienza di programmazione o conoscenza approfondita di Julia, potrebbe essere difficile costruire un grafo delle conoscenze da zero. Ti consiglio di cercare tutorial o guide online e di esercitarti su piccoli progetti prima di cercare di costruire un grafo delle conoscenze completo.
|
assistant
|
it
| 3 | true | false | 0 | false | null |
{
"toxicity": 0.00024336509522981942,
"severe_toxicity": 0.0009542806074023247,
"obscene": 0.006883041001856327,
"identity_attack": 0.0010707102483138442,
"insult": 0.006087493617087603,
"threat": 0.0005237025325186551,
"sexual_explicit": 0.00026877838536165655
}
|
e4a0ccef-2dea-4d30-a648-fd1bd5937689
|
ready_for_export
|
{
"name": [
"+1",
"_skip_labeling"
],
"count": [
1,
1
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.9166666666666666,
0.25,
0.25,
0.75,
0.75,
0
],
"count": [
3,
1,
3,
1,
1,
1,
1,
3,
1,
1,
1,
1,
1
]
}
|
04c2214a-95ca-4ec1-bf80-99b3652f278f
|
e4a0ccef-2dea-4d30-a648-fd1bd5937689
|
3390b131-ad01-4fc3-b18e-e108931d934e
|
2023-02-12T12:55:33.676021+00:00
|
La costruzione di un grafo delle conoscenze a partire da una raccolta di articoli in formato PDF richiede alcune conoscenze di programmazione e di tecniche di analisi dei dati. Tuttavia, se hai alcuni rudimenti di Fortran, potresti avere la capacità di apprendere altri linguaggi di programmazione come Julia. Ecco una possibile procedura generale che puoi seguire:
Installa Julia e un IDE (Integrated Development Environment) come Visual Studio Code o Juno.
Acquisisci familiarità con i pacchetti Julia per l'elaborazione dei file PDF, come PDFIO.jl o PDFTools.jl.
Utilizza questi pacchetti per estrarre il testo dai tuoi documenti PDF.
Prepara i dati per l'analisi, che potrebbe includere la rimozione delle parole vuote, la normalizzazione del testo e la suddivisione del testo in frasi o paragrafi.
Utilizza un algoritmo di estrazione di parole chiave come Textrank per identificare le parole chiave più importanti in ciascun documento.
Utilizza un algoritmo di estrazione di entità come Named Entity Recognition (NER) per identificare i nomi propri, le organizzazioni e gli altri tipi di entità nei documenti.
Utilizza un algoritmo di clustering come K-means o DBSCAN per raggruppare i documenti in base alle parole chiave o alle entità.
Costruisci il grafo delle conoscenze utilizzando una libreria di grafici come LightGraphs.jl o Graphs.jl. Assegna un nodo per ogni documento e collega i nodi in base alle parole chiave o alle entità.
Utilizza una libreria di visualizzazione come GraphPlot.jl o Makie.jl per visualizzare il grafo delle conoscenze.
Si noti che questa è solo una possibile procedura generale e può essere necessario personalizzarla in base alle tue specifiche esigenze e conoscenze di programmazione. Inoltre, può richiedere tempo e sforzo per imparare le tecniche di analisi dei dati necessarie per completare questo progetto.
Se avessi bisogno di ulteriori informazioni o di un aiuto per approfondire meglio l'argomento sono qui per te!
|
assistant
|
it
| 3 | true | false | 1 | false | null |
{
"toxicity": 0.0004738728457596153,
"severe_toxicity": 0.007425458636134863,
"obscene": 0.04629683867096901,
"identity_attack": 0.00839207973331213,
"insult": 0.04355855658650398,
"threat": 0.00236877822317183,
"sexual_explicit": 0.0019294790690764785
}
|
e4a0ccef-2dea-4d30-a648-fd1bd5937689
|
ready_for_export
|
{
"name": [
"+1"
],
"count": [
1
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.25,
0.125,
0.25,
0.375,
0.25,
0
],
"count": [
3,
2,
3,
2,
2,
2,
2,
3,
2,
2,
2,
2,
2
]
}
|
58e8ef62-a705-475a-8cd4-8478fd27db42
|
e4a0ccef-2dea-4d30-a648-fd1bd5937689
|
df411b83-5030-4708-bf81-0fe9fa1398b2
|
2023-02-13T08:36:09.740431+00:00
|
Puoi creare un grafo delle conoscenze da zero con la programmazione in Julia usando una libreria come PyGraphviz. PyGraphviz è una libreria che fornisce un modo semplice e intuitivo per creare grafici a partire da dati. Puoi usare la sintassi di PyGraphviz per creare un grafo dai tuoi dati PDF e quindi visualizzarlo in una forma facilmente comprensibile. Una volta creato il grafo, puoi usare la libreria per calcolare alcune delle sue proprietà, come la distanza tra nodi e il numero di connessioni.
|
assistant
|
it
| 3 | true | false | 2 | false | null |
{
"toxicity": 0.00030765595147386193,
"severe_toxicity": 0.006860255263745785,
"obscene": 0.04172006621956825,
"identity_attack": 0.006580778397619724,
"insult": 0.03808565065264702,
"threat": 0.002498815068975091,
"sexual_explicit": 0.001821447629481554
}
|
e4a0ccef-2dea-4d30-a648-fd1bd5937689
|
ready_for_export
|
{
"name": [
"+1",
"_skip_labeling"
],
"count": [
1,
1
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.6666666666666666,
0.25,
0.16666666666666666,
0.75,
0.16666666666666666,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
e4a729f4-fe59-4379-ab3a-008c2cfa89e3
| null |
f84ba408-4403-4609-b070-908bd2865e6d
|
2023-02-09T20:32:38.070613+00:00
|
Llista de comarques de Catalunya
|
prompter
|
ca
| 3 | true | false | null | false | null | null |
e4a729f4-fe59-4379-ab3a-008c2cfa89e3
|
ready_for_export
|
{
"name": [
"+1",
"_skip_reply"
],
"count": [
4,
1
]
}
|
{
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0.75,
0.25,
0.25,
0.4166666666666667,
0.16666666666666666
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
d7f9e9e8-2c49-444a-9dca-502bae587f7c
|
e4a729f4-fe59-4379-ab3a-008c2cfa89e3
|
508f5a74-97ac-4a64-8a9d-46bd3208f7b5
|
2023-02-10T11:48:10.104798+00:00
|
Les 41 comarques de Catalunya són aquestes:
Alt Camp, Alt Empordà, Alt Penedès, Alt Urgell, Alta Ribagorça, Anoia, Bages, Baix Camp, Baix Ebre, Baix Empordà, Baix Llobregat, Baix Penedès, Barcelonès, Berguedà, Cerdanya, Conca de Barberà, Garraf, Garrigues, Garrotxa, Gironès, Maresme, Montsià, Noguera, Osona, Pallars Jussà, Pallars Sobirà, Pla de l'Estany, Pla d'Urgell, Priorat, Ribera d'Ebre, Ripollès, Segarra, Segrià, Selva, Solsonès, Tarragonès, Terra Alta, Urgell, Vall d'Aran, Vallès Occidental i Vallès Oriental.
|
assistant
|
ca
| 3 | true | false | 0 | false | null | null |
e4a729f4-fe59-4379-ab3a-008c2cfa89e3
|
ready_for_export
| null |
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.5,
0,
0,
0.75,
0.25,
0
],
"count": [
3,
1,
3,
1,
1,
1,
1,
3,
1,
1,
1,
1,
1
]
}
|
49743401-6be5-4f44-8867-db79e0b93ca7
|
e4a729f4-fe59-4379-ab3a-008c2cfa89e3
|
9c795130-368f-4534-88cf-6a1b4717fc2f
|
2023-02-09T21:02:52.991862+00:00
|
A continuació es mostra una llista de les comarques de Catalunya:
- Alt Empordà
- Alta Ribagorça
- Anoia
- Bages
- Baix Camp
- Baix Empordà
- Baix Llobregat
- Baix Penedès
- Barcelonès
- Berguedà
- Cerdanya
- Conca de Barberà
- Garraf
- Gironès
- Maresme
- Montsià
- Noguera
- Osona
- Pallars Jussà
- Pallars Sobirà
- Pla d'Urgell
- Pla de l'Estany
- Priorat
- Ribera d'Ebre
- Ripollès
- Segarra
- Solsonès
- Tarragonès
- Terra Alta
- Urgell
- Vallès Occidental
- Vallès Oriental
|
assistant
|
ca
| 3 | true | false | 1 | false | null | null |
e4a729f4-fe59-4379-ab3a-008c2cfa89e3
|
ready_for_export
|
{
"name": [
"+1"
],
"count": [
3
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
1,
0.08333333333333333,
0.16666666666666666,
1,
0.16666666666666666,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
ebb6822c-d88d-4757-917c-da2a1481c847
|
e4a729f4-fe59-4379-ab3a-008c2cfa89e3
|
d768ee2f-8492-4756-a951-f2801a8290db
|
2023-02-09T21:35:41.474867+00:00
|
Aquí tens la llista de les comarques de Catalunya sense l’article i ordenades alfabèticament:
Alt Camp
Alt Empordà
Alt Penedès
Alt Urgell
Alta Ribagorça
Anoia
Bages
Baix Camp
Baix Ebre
Baix Empordà
Baix Llobregat
Baix Penedès
Barcelonès
Berguedà
Cerdanya
Conca de Barberà
Garraf
Garrigues
Garrotxa
Gironès
Maresme
Moianès
Montsià
Noguera
Osona
Pallars Jussà
Pallars Sobirà
Pla de l'Estany
Pla d'Urgell
Priorat
Ribera d'Ebre
Ripollès
Segarra
Segrià
Selva
Solsonès
Tarragonès
Terra Alta
Urgell
Vall d'Aran
Vallès Occidental
Vallès Oriental
|
assistant
|
ca
| 3 | true | false | 2 | false | null | null |
e4a729f4-fe59-4379-ab3a-008c2cfa89e3
|
ready_for_export
|
{
"name": [
"+1"
],
"count": [
2
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.8333333333333334,
0.16666666666666666,
0.25,
1,
0.16666666666666666,
0.16666666666666666
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
e4afcd70-a5f9-480a-bfc4-8ebfd3fe744e
| null |
ffbf2ba4-b83f-4e20-b61c-dbded6e4ed89
|
2023-02-13T18:23:09.548632+00:00
|
Cómo puedo hacer unas luces inteligentes con las ws2812b utilizando un Esp8266
|
prompter
|
es
| 3 | true | false | null | false | null |
{
"toxicity": 0.000998611212708056,
"severe_toxicity": 0.005229185800999403,
"obscene": 0.037858325988054276,
"identity_attack": 0.007347735110670328,
"insult": 0.03622936084866524,
"threat": 0.0020206323824822903,
"sexual_explicit": 0.0012807814637199044
}
|
e4afcd70-a5f9-480a-bfc4-8ebfd3fe744e
|
ready_for_export
|
{
"name": [
"+1",
"_skip_ranking"
],
"count": [
4,
3
]
}
|
{
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0.45,
0.0625,
0.125,
0.5,
0
],
"count": [
4,
3,
3,
3,
3,
3,
5,
4,
4,
5,
4
]
}
|
2bdcfbba-2ebb-421e-b4c4-ddb9f660d9ac
|
e4afcd70-a5f9-480a-bfc4-8ebfd3fe744e
|
9513d9ba-fca7-4a47-b818-9e6bcc778131
|
2023-02-27T10:22:38.235470+00:00
|
En primer lugar necesitaras varios componentes:
* NodeMcu ESP8266 cp2102
* Tira led de WS2812B 1m PCB White 30leds/m no waterproof
* Convertidor de Nivel Logico 3.3v a 5v Bidirecccional (Level Converter)
* Fuente Alimentacion 5v 8A 40W
Ademas, tendras que programar un Controlador:
Nos ayudaremos de la libreria de Neopixel de Adafruit.
En Platformio la libreria es la nº28.
Y usaremos su código de ejemplo (tendremos que cambiar solamente el pin de control que pongamos (PIN), y el numero de leds a controlar (NUMPIXELS):
```
// NeoPixel Ring simple sketch (c) 2013 Shae Erisson
// released under the GPLv3 license to match the rest of the AdaFruit NeoPixel library
#include <Adafruit_NeoPixel.h>
#ifdef __AVR__
#include <avr/power.h>
#endif
// Which pin on the Arduino is connected to the NeoPixels?
// On a Trinket or Gemma we suggest changing this to 1
#define PIN 6
// How many NeoPixels are attached to the Arduino?
#define NUMPIXELS 16
// When we setup the NeoPixel library, we tell it how many pixels, and which pin to use to send signals.
// Note that for older NeoPixel strips you might need to change the third parameter--see the strandtest
// example for more information on possible values.
Adafruit_NeoPixel pixels = Adafruit_NeoPixel(NUMPIXELS, PIN, NEO_GRB + NEO_KHZ800);
int delayval = 500; // delay for half a second
void setup() {
// This is for Trinket 5V 16MHz, you can remove these three lines if you are not using a Trinket
#if defined (__AVR_ATtiny85__)
if (F_CPU == 16000000) clock_prescale_set(clock_div_1);
#endif
// End of trinket special code
pixels.begin(); // This initializes the NeoPixel library.
}
void loop() {
// For a set of NeoPixels the first NeoPixel is 0, second is 1, all the way up to the count of pixels minus one.
for(int i=0;i<NUMPIXELS;i++){
// pixels.Color takes RGB values, from 0,0,0 up to 255,255,255
pixels.setPixelColor(i, pixels.Color(0,150,0)); // Moderately bright green color.
pixels.show(); // This sends the updated pixel color to the hardware.
delay(delayval); // Delay for a period of time (in milliseconds).
}
}
```
Aqui tienes otro ejemplo, Efecto Arcoiris:
```
#include <Adafruit_NeoPixel.h>
// constants won't change. They're used here to
// set pin numbers:
const int ledPin = 4; // the number of the neopixel strip
const int numLeds = 30;
//Adafruit_NeoPixel pixels = Adafruit_NeoPixel(8, ledPin);
Adafruit_NeoPixel strip = Adafruit_NeoPixel(numLeds, ledPin, NEO_GRB + NEO_KHZ800);
// Input a value 0 to 255 to get a color value.
// The colours are a transition r - g - b - back to r.
uint32_t Wheel(byte WheelPos) {
if(WheelPos < 85) {
return strip.Color(WheelPos * 3, 255 - WheelPos * 3, 0);
}
else if(WheelPos < 170) {
WheelPos -= 85;
return strip.Color(255 - WheelPos * 3, 0, WheelPos * 3);
}
else {
WheelPos -= 170;
return strip.Color(0, WheelPos * 3, 255 - WheelPos * 3);
}
}
void rainbow(uint8_t wait) {
uint16_t i, j;
for(j=0; j<256; j++) {
for(i=0; i<strip.numPixels(); i++) {
strip.setPixelColor(i, Wheel((i*1+j) & 255));
}
strip.show();
delay(wait);
}
}
void setup() {
strip.begin();
strip.setBrightness(80); // 1/3 brightness
}
void loop() {
rainbow(30);
delay(10);
}
```
|
assistant
|
es
| 3 | true | false | 0 | false | null |
{
"toxicity": 0.00025439177989028394,
"severe_toxicity": 0.0012942058965563774,
"obscene": 0.007584922015666962,
"identity_attack": 0.0018126252107322216,
"insult": 0.005165493115782738,
"threat": 0.0005349882994778454,
"sexual_explicit": 0.0002748996193986386
}
|
e4afcd70-a5f9-480a-bfc4-8ebfd3fe744e
|
ready_for_export
|
{
"name": [
"_skip_labeling"
],
"count": [
8
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.8333333333333334,
0.08333333333333333,
0,
0.8333333333333334,
0.8333333333333334,
0.08333333333333333
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
39d4498d-0460-4f64-854f-3ab32d31eb3f
|
e4afcd70-a5f9-480a-bfc4-8ebfd3fe744e
|
0b58e558-15f0-4032-9d15-e669c2a4b61f
|
2023-02-27T04:54:33.245972+00:00
|
Para realizar esta tarea se requieren conocimientos tanto de instalaciones eléctricas como de programación. Además, dependiendo como se quiera instalar la tira de leds y utilizar el funcionamiento de la aplicación puede cambiar el programa.
Para un caso genérico, la instalación del Hardware debe ser la siguiente:
Conecta el ws2812b a una fuente de 5V, con 60mA por cada led en la tira. Conecta el pin de control del Esp8266 a una resistencia de 470 Ohms, y de allí al pin de control del ws2812b. Luego, debes conectar los pines de tierra tanto del ws2812b como el Esp8266.
Para la programación de software podemos utilizar el IDE de Arduino, y la librería FastLED:
#include "FastLED.h"
#define Num_Leds 60
#define Control_Pin 12
CRGB tira[Num_Leds];
void setup(){
FastLED.addLeds<WS2818B, Control_Pin, RGB>(tira, Num_Leds);
}
void loop(){
//Animación sencilla, prende todos los leds en rojo en orden ascendente y luego los apaga en orden descendiente:
for(int i =0; i<Num_Leds; i++)
tira[i] = CRGB::Red; FastLed.show(); delay(30);
for(int i =0; i<Num_Leds; i++)
tira[Num_Leds - i - 1] = CRGB::Black; FastLed.show(); delay(30);
}
Considerando que se esta utilizando un Esp8266 que tiene capacidades de red, se puede considerar utilizar estas para controlar las luces inteligentes.
|
assistant
|
es
| 3 | true | false | 1 | false | null |
{
"toxicity": 0.00032130631734617054,
"severe_toxicity": 0.007069948595017195,
"obscene": 0.04037396237254143,
"identity_attack": 0.007334205321967602,
"insult": 0.035156190395355225,
"threat": 0.002544885966926813,
"sexual_explicit": 0.0013566924026235938
}
|
e4afcd70-a5f9-480a-bfc4-8ebfd3fe744e
|
ready_for_export
|
{
"name": [
"+1",
"_skip_labeling"
],
"count": [
1,
1
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0.3333333333333333,
0,
0,
0,
0,
0,
0.5833333333333334,
0,
0,
0.5833333333333334,
0.4166666666666667,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
ab91f6b6-4070-4f38-8efb-3bbd90437f03
|
e4afcd70-a5f9-480a-bfc4-8ebfd3fe744e
|
1b763adf-438e-4998-824c-e95f343d2280
|
2023-02-27T05:32:39.919539+00:00
|
Cuando se refiere a objetos, el adjetivo "inteligente" implica un significado metafórico y abstracto en la mayoría de los casos. Para brindarte la mejor respuesta posible, por favor especifica cuáles son tus expectativas acerca de las características o cualidades específicas que en el contexto de tu pregunta, deben poseer las luces, para ser consideradas como inteligentes.
|
assistant
|
es
| 3 | true | false | 2 | false | null |
{
"toxicity": 0.0007099020876921713,
"severe_toxicity": 0.000025627490686019883,
"obscene": 0.00028585243853740394,
"identity_attack": 0.00008531265484634787,
"insult": 0.0006728788139298558,
"threat": 0.00002446815778966993,
"sexual_explicit": 0.000026730811441666447
}
|
e4afcd70-a5f9-480a-bfc4-8ebfd3fe744e
|
ready_for_export
|
{
"name": [
"_skip_labeling"
],
"count": [
1
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.4375,
0.08333333333333333,
0,
0.25,
0.16666666666666666,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
4,
3,
3,
4,
3,
3
]
}
|
e4b7c348-6b89-4d84-9670-9ac7d7a2f6cf
| null |
90d30ba9-c38f-4a75-939b-581035665ea8
|
2023-02-24T15:11:47.591064+00:00
|
Explicame la arquitectura Transformer que está detras del modelo de lenguaje GPT y sus diferencias a otras arquitecturas.
|
prompter
|
es
| 3 | true | false | null | false | null |
{
"toxicity": 0.0006987512460909784,
"severe_toxicity": 0.0025205849669873714,
"obscene": 0.02091052569448948,
"identity_attack": 0.00361329666338861,
"insult": 0.017459001392126083,
"threat": 0.001165452878922224,
"sexual_explicit": 0.0005420232191681862
}
|
e4b7c348-6b89-4d84-9670-9ac7d7a2f6cf
|
ready_for_export
|
{
"name": [
"+1",
"_skip_ranking"
],
"count": [
3,
4
]
}
|
{
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0.8333333333333334,
0.08333333333333333,
0.25,
0.6666666666666666,
0.08333333333333333
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
24a8b102-dd18-438e-b358-6a4578498249
|
e4b7c348-6b89-4d84-9670-9ac7d7a2f6cf
|
3a62b815-d5ba-473a-9926-239d5b47d38f
|
2023-06-12T04:16:29.441779+00:00
|
La arquitectura Transformer es un tipo de modelo de red neuronal que se utiliza comúnmente en el campo del Procesamiento del Lenguaje Natural (PLN). Esta arquitectura permite un entrenamiento más eficiente y una mayor capacidad de procesamiento de información que otras arquitecturas de redes neuronales, como las redes recurrentes.
La principal diferencia entre la arquitectura Transformer y otras arquitecturas es el uso de la auto-atención. En lugar de tener una estructura recurrente que procesa la información una entrada a la vez, la auto-atención permite a la red procesar simultáneamente todas las entradas de la secuencia. Esto significa que la red puede procesar la información de manera más efectiva y eficiente, lo que a su vez permite un entrenamiento más rápido y una mejor capacidad para manejar conjuntos de datos más grandes.
La arquitectura Transformer se utiliza comúnmente en modelos de lenguaje como GPT-3 o BERT, ya que estos modelos requieren el procesamiento de grandes cantidades de texto para generar respuestas coherentes. La auto-atención permite a estos modelos analizar y comprender la relación entre las palabras y los patrones de uso del lenguaje en una gran cantidad de datos de entrenamiento y, en última instancia, generar respuestas precisas y coherentes a las preguntas.
En resumen, la arquitectura Transformer es una herramienta poderosa para procesar grandes cantidades de datos en modelos de lenguaje y otros campos del PLN. Su capacidad para procesar toda la información de una secuencia simultáneamente y su eficiencia en el entrenamiento le brindan una ventaja sobre otras arquitecturas de redes neuronales en términos de precisión y eficiencia.
|
assistant
|
es
| 5 | true | false | 0 | false | null |
{
"toxicity": 0.0003809037443716079,
"severe_toxicity": 0.002304499037563801,
"obscene": 0.022301770746707916,
"identity_attack": 0.002724059857428074,
"insult": 0.016769908368587494,
"threat": 0.0010068565607070923,
"sexual_explicit": 0.0007090913713909686
}
|
e4b7c348-6b89-4d84-9670-9ac7d7a2f6cf
|
ready_for_export
|
{
"name": [
"+1",
"_skip_reply",
"_skip_labeling"
],
"count": [
3,
1,
1
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.75,
0,
0,
0.75,
0.2,
0
],
"count": [
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5
]
}
|
2318a40d-13de-4312-bba6-4724bea1379e
|
24a8b102-dd18-438e-b358-6a4578498249
|
92841ff4-91f8-40e3-8c2a-37db9db2f643
|
2023-08-17T10:07:47.638933+00:00
|
Explicamelo con palabras mas sencillas, como si se lo explicases a un niño pequeño.
|
prompter
|
es
| 3 | true | false | null | false | null |
{
"toxicity": 0.0068882121704518795,
"severe_toxicity": 0.00003264001497882418,
"obscene": 0.0005324738449417055,
"identity_attack": 0.0000923652623896487,
"insult": 0.004245496354997158,
"threat": 0.00007889684638939798,
"sexual_explicit": 0.00006261763337533921
}
|
e4b7c348-6b89-4d84-9670-9ac7d7a2f6cf
|
ready_for_export
|
{
"name": [
"+1",
"-1",
"_skip_reply",
"_skip_ranking",
"_skip_labeling"
],
"count": [
1,
1,
2,
7,
1
]
}
|
{
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0.75,
0.25,
0.25,
0.25,
0.25
],
"count": [
3,
3,
1,
1,
1,
1,
3,
1,
1,
1,
1
]
}
|
01177704-fc71-429e-ad94-6fc43f97a1f1
|
2318a40d-13de-4312-bba6-4724bea1379e
|
6c27ad8b-8e4c-4f41-b269-47996a2fce67
|
2023-08-31T20:28:54.198960+00:00
|
¡Claro!
Imagina que estás armando un rompecabezas grande. Cada pieza del rompecabezas es como una palabra en una oración.
Los modelos antiguos, como las redes recurrentes, son como si intentaras armar el rompecabezas poniendo una pieza a la vez, y mirando solo la última pieza que colocaste para decidir dónde va la siguiente. A veces, esto puede hacer que te pierdas y demores mucho en armarlo.
Ahora, la arquitectura Transformer, la que usa GPT, es como si tuvieras unos lentes mágicos que te permiten mirar todas las piezas del rompecabezas al mismo tiempo. Así, puedes ver cómo encajan todas juntas y armas el rompecabezas mucho más rápido y mejor.
Entonces, en el mundo de las computadoras y las palabras, el Transformer ayuda a las máquinas a entender mejor las oraciones porque puede mirar todas las palabras a la vez, no solo una por una. ¡Y eso lo hace especial!
|
assistant
|
es
| 3 | true | false | 0 | false | null |
{
"toxicity": 0.0005228102672845125,
"severe_toxicity": 0.000048960115236695856,
"obscene": 0.00047435142914764583,
"identity_attack": 0.0000892883472261019,
"insult": 0.00033930258359760046,
"threat": 0.0000737515147193335,
"sexual_explicit": 0.0000459404727735091
}
|
e4b7c348-6b89-4d84-9670-9ac7d7a2f6cf
|
ready_for_export
| null |
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.9166666666666666,
0,
0.3333333333333333,
1,
1,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
36d53c62-ae9e-424e-b942-5e2c853e4a1d
|
2318a40d-13de-4312-bba6-4724bea1379e
|
9c178150-c8bc-4e51-8df2-3af2e0293061
|
2023-09-06T18:40:20.211922+00:00
|
xplicame la arquitectura Transformer que está detras del modelo de lenguaje GPT y sus diferencias a otras arquitecturas.
|
assistant
|
es
| 3 | true | false | 1 | false | null |
{
"toxicity": 0.0008886022260412574,
"severe_toxicity": 0.003137990366667509,
"obscene": 0.024664776399731636,
"identity_attack": 0.004643183201551437,
"insult": 0.020767025649547577,
"threat": 0.001530603040009737,
"sexual_explicit": 0.0006019739084877074
}
|
e4b7c348-6b89-4d84-9670-9ac7d7a2f6cf
|
ready_for_export
| null |
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
1,
0,
0,
0.6666666666666666,
0,
0,
0,
0.3333333333333333,
0.3333333333333333,
0,
0,
0.08333333333333333
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
ae5009c7-27bc-444c-9166-0990ba91b8d6
|
e4b7c348-6b89-4d84-9670-9ac7d7a2f6cf
|
f238ea8c-4309-4d5a-8e0e-698fd54749f5
|
2023-07-20T17:03:26.454993+00:00
|
Claro. La arquitectura Transformer es un modelo de aprendizaje automático que se utiliza para el procesamiento del lenguaje natural. Fue introducido por primera vez en el artículo "Attention Is All You Need" de Vaswani et al. (2017).
El transformador es una arquitectura de red neuronal que utiliza un mecanismo de atención para aprender relaciones entre diferentes partes de una secuencia de entrada. La atención es un proceso que permite a la red neuronal enfocarse en diferentes partes de la entrada y de la salida en diferentes momentos de la ejecución. Esto permite al transformador aprender relaciones más complejas entre diferentes partes de una secuencia de entrada que otros modelos de aprendizaje automático.
El transformador ha demostrado ser muy eficaz para una variedad de tareas de procesamiento del lenguaje natural, incluyendo traducción automática, resumen de texto, respuesta a preguntas y generación de texto. También se ha utilizado para tareas de aprendizaje automático de visión por computadora, como la clasificación de imágenes y la detección de objetos.
El transformador tiene algunas ventajas significativas sobre otras arquitecturas de modelos de lenguaje. En primer lugar, es muy eficiente en términos de tiempo de entrenamiento y tiempo de ejecución. Esto se debe a que utiliza un mecanismo de atención que es muy eficiente en términos computacionales. En segundo lugar, el transformador es muy eficaz para aprender relaciones a largo plazo entre diferentes partes de una secuencia de entrada. Esto se debe a que utiliza un mecanismo de atención que le permite mirar a cualquier parte de la secuencia de entrada, independientemente de su posición.
El transformador ha tenido un impacto significativo en el campo del procesamiento del lenguaje natural. Ha permitido a los investigadores desarrollar modelos de lenguaje que son más eficaces que cualquier otro modelo anterior. El transformador también se ha utilizado para desarrollar nuevos métodos para otras tareas de aprendizaje automático, como la visión por computadora.
|
assistant
|
es
| 3 | true | false | 1 | false | null |
{
"toxicity": 0.0003437904524616897,
"severe_toxicity": 0.002561307977885008,
"obscene": 0.022779442369937897,
"identity_attack": 0.002743971301242709,
"insult": 0.01933194324374199,
"threat": 0.0009956572903320193,
"sexual_explicit": 0.0007533901371061802
}
|
e4b7c348-6b89-4d84-9670-9ac7d7a2f6cf
|
ready_for_export
|
{
"name": [
"+1",
"_skip_labeling"
],
"count": [
1,
4
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.5833333333333334,
0.08333333333333333,
0.4166666666666667,
0.5833333333333334,
0.4166666666666667,
0.08333333333333333
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
4c855c15-2b77-4547-9911-a10c51980bec
|
ae5009c7-27bc-444c-9166-0990ba91b8d6
|
2c84ac51-fef8-4d0f-9c73-5db4dcc2be01
|
2023-08-03T22:28:02.856846+00:00
|
Gracias, podrías resumirlo por favor.
|
prompter
|
es
| 3 | true | false | null | false | null |
{
"toxicity": 0.0005320925847627223,
"severe_toxicity": 0.0033637292217463255,
"obscene": 0.02584700472652912,
"identity_attack": 0.003951787017285824,
"insult": 0.021694118157029152,
"threat": 0.0015081499004736543,
"sexual_explicit": 0.0008198785362765193
}
|
e4b7c348-6b89-4d84-9670-9ac7d7a2f6cf
|
ready_for_export
|
{
"name": [
"+1"
],
"count": [
1
]
}
|
{
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0.5,
0,
0.25,
0.25,
0
],
"count": [
3,
3,
2,
2,
2,
2,
3,
2,
2,
2,
2
]
}
|
a6bdba8e-29b2-452f-90fc-d5b699ef736f
|
e4b7c348-6b89-4d84-9670-9ac7d7a2f6cf
|
5769c35d-6293-461d-b8da-7b993ef51775
|
2023-06-11T22:54:55.454199+00:00
|
La arquitectura Transformer es una arquitectura de red neuronal que utiliza la atención como mecanismo principal para procesar secuencias de datos, como el texto o el habla. Fue introducida en 2017 por Google AI en el artículo “Attention is All You Need”. La arquitectura Transformer se basa en dos componentes principales: el codificador y el decodificador. El codificador recibe una secuencia de entrada (por ejemplo, una oración en un idioma) y la transforma en una representación vectorial de alto nivel. El decodificador recibe esta representación y genera una secuencia de salida (por ejemplo, una traducción en otro idioma). Tanto el codificador como el decodificador están formados por varias capas de bloques idénticos que contienen capas de atención y redes feed-forward.
El modelo de lenguaje GPT es un modelo basado en la arquitectura Transformer que se entrena de forma autoregresiva para predecir la siguiente palabra dada una secuencia de palabras anteriores. El modelo GPT se pre-entrena con enormes cantidades de texto sin etiquetar para aprender las propiedades estadísticas del lenguaje natural. Luego, se puede afinar para realizar diferentes tareas específicas, como generación de texto, comprensión lectora o respuesta a preguntas.
La principal diferencia entre GPT y otras arquitecturas basadas en Transformer es que GPT solo utiliza el decodificador del Transformer, mientras que otras arquitecturas, como BERT o T5, utilizan tanto el codificador como el decodificador. Esto se debe a que GPT está diseñado para generar texto de forma unidireccional, es decir, solo tiene en cuenta el contexto anterior a la palabra que se quiere predecir. Por el contrario, otras arquitecturas pueden tener en cuenta el contexto bidireccional (anterior y posterior) o incluso modificar la secuencia de entrada para adaptarse a diferentes tareas.
|
assistant
|
es
| 5 | true | false | 2 | false | null |
{
"toxicity": 0.0002921168925240636,
"severe_toxicity": 0.0045859115198254585,
"obscene": 0.0326584130525589,
"identity_attack": 0.004783455282449722,
"insult": 0.02585178054869175,
"threat": 0.0016406953800469637,
"sexual_explicit": 0.0011324454098939896
}
|
e4b7c348-6b89-4d84-9670-9ac7d7a2f6cf
|
ready_for_export
|
{
"name": [
"+1",
"_skip_labeling"
],
"count": [
4,
1
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.75,
0.2,
0.2,
0.75,
0.4,
0.2
],
"count": [
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5,
5
]
}
|
52be7002-3f80-40b1-8b89-97156e9fd896
|
a6bdba8e-29b2-452f-90fc-d5b699ef736f
|
312e8499-d8a0-4753-b8a3-3be674b1d1c4
|
2023-07-12T19:58:02.207690+00:00
|
Muchas gracias, ¿Podrías explicarme como usaron esta nueva arquitectura en otros aplicativos como el apredizaje por refuerzo?
|
prompter
|
es
| 3 | true | false | null | false | null |
{
"toxicity": 0.00045948001206852496,
"severe_toxicity": 0.00463210279121995,
"obscene": 0.03322329744696617,
"identity_attack": 0.005767145659774542,
"insult": 0.02928871661424637,
"threat": 0.0018074713880196214,
"sexual_explicit": 0.0009659058414399624
}
|
e4b7c348-6b89-4d84-9670-9ac7d7a2f6cf
|
ready_for_export
|
{
"name": [
"_skip_reply",
"_skip_ranking",
"_skip_labeling"
],
"count": [
2,
2,
1
]
}
|
{
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0.8333333333333334,
0,
0,
0.625,
0
],
"count": [
3,
3,
2,
2,
2,
2,
3,
2,
2,
2,
2
]
}
|
1157cdfa-3357-4a88-bb0d-5d08c9d249cd
|
52be7002-3f80-40b1-8b89-97156e9fd896
|
dae1fa6f-49d1-4cc6-b67d-d205e9203aca
|
2023-08-23T01:09:23.919578+00:00
|
Claro, te explicaré cómo la arquitectura Transformer se ha aplicado en el aprendizaje por refuerzo, específicamente en el contexto del algoritmo DQN (Deep Q-Network), que es una técnica fundamental en este campo.
El DQN es un algoritmo que utiliza redes neuronales profundas para aproximar la función Q, que mapea estados y acciones a sus valores de recompensa esperados a largo plazo. Tradicionalmente, las redes neuronales convolucionales se han utilizado para aprender estas funciones Q en juegos de video.
Sin embargo, se ha demostrado que las redes convolucionales tienen dificultades para capturar relaciones espaciales y temporales complejas en entornos más complejos. Aquí es donde entra la arquitectura Transformer para mejorar el DQN.
En lugar de usar capas convolucionales, el DQN con arquitectura Transformer utiliza capas de atención multi-cabeza. Cada estado y acción se representa como un vector y se pasa a través de estas capas de atención. Cada cabeza de atención en el Transformer captura diferentes tipos de relaciones entre estados y acciones, lo que permite capturar relaciones más complejas y a largo plazo.
Además, se utiliza la técnica de "self-attention", donde un estado o acción puede prestar atención a otros estados o acciones dentro de la misma secuencia. Esto permite al modelo aprender relaciones no lineales entre las características y capturar dependencias a largo plazo en las secuencias de acciones y estados.
Otro componente clave es la incorporación de la función de recompensa en el proceso de atención. La recompensa es tratada como una entrada adicional que se utiliza para ajustar la atención en función de su valor, lo que ayuda al modelo a enfocarse en partes relevantes del estado o acción para mejorar la toma de decisiones.
En resumen, la aplicación de la arquitectura Transformer en el aprendizaje por refuerzo, específicamente en el DQN, permite capturar relaciones espaciales y temporales más complejas en entornos de aprendizaje por refuerzo. Las capas de atención multi-cabeza y la atención "self-attention" mejoran la capacidad del modelo para aprender dependencias a largo plazo y relaciones no lineales, lo que conduce a una toma de decisiones más precisa y mejor rendimiento en tareas de aprendizaje por refuerzo.
|
assistant
|
es
| 3 | true | false | 0 | false | null |
{
"toxicity": 0.0003017689741682261,
"severe_toxicity": 0.0005927964230068028,
"obscene": 0.00591691117733717,
"identity_attack": 0.0007716185064055026,
"insult": 0.004620173946022987,
"threat": 0.000300917134154588,
"sexual_explicit": 0.0002330776333110407
}
|
e4b7c348-6b89-4d84-9670-9ac7d7a2f6cf
|
ready_for_export
| null |
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.5833333333333334,
0.16666666666666666,
0.08333333333333333,
0.5833333333333334,
0.16666666666666666,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
562922fe-144a-48e5-9011-2992a69d9b14
|
1157cdfa-3357-4a88-bb0d-5d08c9d249cd
|
62419e05-4926-48b2-b04d-ea6cb7671acc
|
2023-09-26T03:10:45.647039+00:00
|
dame ocho oraciones en inglés sobre mi futuro usando going to
|
prompter
|
es
| 3 | true | false | null | false | null |
{
"toxicity": 0.0028103867080062628,
"severe_toxicity": 0.0027457440737634897,
"obscene": 0.028892137110233307,
"identity_attack": 0.004141501151025295,
"insult": 0.023838046938180923,
"threat": 0.0012933248654007912,
"sexual_explicit": 0.0009768244344741106
}
|
e4b7c348-6b89-4d84-9670-9ac7d7a2f6cf
|
ready_for_export
|
{
"name": [
"+1"
],
"count": [
1
]
}
|
{
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0.3333333333333333,
0,
0,
0.3333333333333333,
0,
0,
0.3333333333333333,
0.25,
0.16666666666666666,
0.16666666666666666,
0.16666666666666666
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
db6c5399-3568-4ee8-b535-2ca6dc265d61
|
52be7002-3f80-40b1-8b89-97156e9fd896
|
6c27ad8b-8e4c-4f41-b269-47996a2fce67
|
2023-08-31T18:36:19.574873+00:00
|
Claro, la arquitectura Transformer ha demostrado ser muy versátil y se ha extendido más allá del procesamiento del lenguaje natural (NLP, por sus siglas en inglés) para aplicaciones como el aprendizaje por refuerzo. Aunque el aprendizaje por refuerzo y el procesamiento del lenguaje natural pueden parecer dominios bastante distintos, comparten ciertas características fundamentales: ambos implican el procesamiento secuencial de información y la toma de decisiones en función de un estado o contexto.
En el aprendizaje por refuerzo, un agente aprende a realizar acciones en un entorno con el objetivo de maximizar alguna noción de recompensa acumulativa. Los Transformers pueden ser útiles aquí de varias maneras:
1. **Representación del Estado**: El agente podría utilizar un Transformer para procesar la información del entorno y generar una representación más rica del estado en el que se encuentra. Esta representación podría utilizarse para tomar decisiones más informadas.
2. **Política del Agente**: Se podría usar un modelo Transformer para representar la política del agente, que mapea estados a acciones. El modelo podría tomar el estado actual (y posiblemente también estados pasados) como entrada y producir una distribución de probabilidad sobre las acciones posibles como salida.
3. **Modelo del Entorno**: También es posible utilizar Transformers para aprender un modelo del entorno, que el agente podría luego utilizar para planificar o simular experiencias futuras.
4. **Multi-agente y Comunicación**: En escenarios donde hay múltiples agentes interactuando, los Transformers pueden ser útiles para modelar las complejas dinámicas sociales o incluso para permitir una forma de comunicación entre los agentes.
5. **Transferencia de Conocimiento**: Dado que los Transformers son buenos para capturar relaciones a largo plazo y dependencias complejas, podrían ayudar a transferir el conocimiento aprendido en una tarea a otra tarea relacionada, algo que es muy útil en el aprendizaje por refuerzo, donde el entrenamiento puede ser muy costoso.
En resumen, aunque la arquitectura Transformer se diseñó originalmente para tareas de procesamiento del lenguaje natural, su capacidad para manejar secuencias y su eficiencia en el aprendizaje de representaciones la hacen muy útil en una amplia variedad de aplicaciones, incluido el aprendizaje por refuerzo.
|
assistant
|
es
| 3 | true | false | 1 | false | null |
{
"toxicity": 0.0002944002626463771,
"severe_toxicity": 0.0006395945674739778,
"obscene": 0.006521749310195446,
"identity_attack": 0.0008360262145288289,
"insult": 0.004732093308120966,
"threat": 0.0003226105181965977,
"sexual_explicit": 0.0002368896675761789
}
|
e4b7c348-6b89-4d84-9670-9ac7d7a2f6cf
|
ready_for_export
|
{
"name": [
"+1",
"_skip_labeling"
],
"count": [
1,
2
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.5833333333333334,
0.25,
0.16666666666666666,
0.6666666666666666,
0.4166666666666667,
0.16666666666666666
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
e4b7d1fa-7ebe-44ca-9fdf-c604e832ccb7
| null |
bab4cf56-9a84-476e-bdef-0f30f425cd87
|
2023-02-08T10:54:50.261841+00:00
|
якою мовою розмовляють у Сирії?
|
prompter
|
uk-UA
| 3 | true | false | null | false | null | null |
e4b7d1fa-7ebe-44ca-9fdf-c604e832ccb7
|
ready_for_export
| null |
{
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
1,
0,
0,
0.3333333333333333,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
7a23b968-df57-46a3-bbb6-09d1210771f2
|
e4b7d1fa-7ebe-44ca-9fdf-c604e832ccb7
|
24b066c3-b0b2-4af0-9bc2-d15c29b6e9a6
|
2023-02-09T19:44:05.018806+00:00
|
Державною мовою Сирії є арабська. Також у Сирії розмовляють курдською, вірменською, арамейською, черкеською, англійською та французькою мовами.
|
assistant
|
uk-UA
| 3 | true | false | 0 | false | null | null |
e4b7d1fa-7ebe-44ca-9fdf-c604e832ccb7
|
ready_for_export
|
{
"name": [
"+1"
],
"count": [
1
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
1,
0,
0.16666666666666666,
1,
0.3333333333333333,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
156cb4e3-910c-4434-9856-1f391b493e8a
|
7a23b968-df57-46a3-bbb6-09d1210771f2
|
24b066c3-b0b2-4af0-9bc2-d15c29b6e9a6
|
2023-02-15T14:40:26.937009+00:00
|
В яких країнах також розмовляють арамейською?
|
prompter
|
uk-UA
| 3 | true | false | null | false | null | null |
e4b7d1fa-7ebe-44ca-9fdf-c604e832ccb7
|
ready_for_export
| null |
{
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0.9166666666666666,
0,
0.16666666666666666,
0.16666666666666666,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
eea3ab43-e523-4557-b479-31604677bee2
|
e4b7d1fa-7ebe-44ca-9fdf-c604e832ccb7
|
afc1303f-a5f5-4622-a2c5-b3546c7f0fe8
|
2023-02-09T20:29:45.523690+00:00
|
У Сирії в основному розмовляють арабською мовою.
|
assistant
|
uk-UA
| 3 | true | false | 1 | false | null | null |
e4b7d1fa-7ebe-44ca-9fdf-c604e832ccb7
|
ready_for_export
|
{
"name": [
"-1"
],
"count": [
1
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.8333333333333334,
0,
0.08333333333333333,
0.75,
0.16666666666666666,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
cf49be4c-265f-41df-8fc9-762d0d0d3294
|
eea3ab43-e523-4557-b479-31604677bee2
|
24b066c3-b0b2-4af0-9bc2-d15c29b6e9a6
|
2023-02-15T14:36:31.532341+00:00
|
А в Йорданії?
|
prompter
|
uk-UA
| 3 | true | false | null | false | null | null |
e4b7d1fa-7ebe-44ca-9fdf-c604e832ccb7
|
ready_for_export
| null |
{
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
1,
0,
0.08333333333333333,
0.16666666666666666,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
de2940c5-deff-4870-998e-1cd15c6cb398
|
cf49be4c-265f-41df-8fc9-762d0d0d3294
|
d0f09472-50b2-4feb-ac16-6a5bc2dccda7
|
2023-02-20T15:31:38.786133+00:00
|
Офіційною мовою є сучасний стандарт арабської мови (англ. Modern Standard Arabic, MSA) — літературна мова, яку викладають у школах. Більшість йорданців розмовляють на діалекті, відомому як йорданська арабська. Англійська, хоч і без офіційного статусу, широко розповсюджена у країні та є де-факто мовою комерції й банкінгу, а також має спів-офіційний статус у сфері освіти: майже всі заняття в університетах проводяться англійською та майже у всіх державних школах викладають англійську на рівні з арабською
|
assistant
|
uk-UA
| 3 | true | false | 0 | false | null | null |
e4b7d1fa-7ebe-44ca-9fdf-c604e832ccb7
|
ready_for_export
|
{
"name": [
"+1"
],
"count": [
1
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
1,
0.125,
0
],
"count": [
3,
2,
3,
2,
2,
2,
2,
3,
2,
2,
2,
2,
2
]
}
|
a9a23344-260b-4bd7-a900-cc9aff28ebc0
|
de2940c5-deff-4870-998e-1cd15c6cb398
|
24b066c3-b0b2-4af0-9bc2-d15c29b6e9a6
|
2023-02-21T17:26:00.902719+00:00
|
Крім сучасного стандарту, які ще існують? Наскільки літературна арабська мова відрізняється від розмовної?
|
prompter
|
uk-UA
| 3 | true | false | null | false | null | null |
e4b7d1fa-7ebe-44ca-9fdf-c604e832ccb7
|
ready_for_export
| null |
{
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
1,
0,
0,
0.25,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
60e24b1e-f57c-4aad-9210-656b7fcee41a
|
cf49be4c-265f-41df-8fc9-762d0d0d3294
|
9c55638f-8e0c-4cf4-b602-32d3dcea2781
|
2023-02-21T11:33:40.405412+00:00
|
В Йорданії офіційною мовою є арабська, але також розповсюджена англійська мова, яка є обов'язковою до вивчення в школах Йорданії
|
assistant
|
uk-UA
| 3 | true | false | 1 | false | null | null |
e4b7d1fa-7ebe-44ca-9fdf-c604e832ccb7
|
ready_for_export
|
{
"name": [
"+1"
],
"count": [
1
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0.3333333333333333,
0,
0,
0,
0,
0,
0.9166666666666666,
0,
0,
0.9166666666666666,
0.08333333333333333,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
f792bc1c-9fc6-4869-af23-5c63a31f53c0
|
e4b7d1fa-7ebe-44ca-9fdf-c604e832ccb7
|
6e5f57d6-9e60-4749-8f1c-19a32b2fc872
|
2023-02-17T11:24:46.690382+00:00
|
Офіційна мова мова у Сирії це Арабська мова
|
assistant
|
uk-UA
| 3 | true | false | 2 | false | null | null |
e4b7d1fa-7ebe-44ca-9fdf-c604e832ccb7
|
ready_for_export
| null |
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.6666666666666666,
0,
0,
0.8333333333333334,
0,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
8fc362d7-e0b5-4f97-bfcf-b52e6f91b5d4
|
f792bc1c-9fc6-4869-af23-5c63a31f53c0
|
24b066c3-b0b2-4af0-9bc2-d15c29b6e9a6
|
2023-02-18T20:00:56.875948+00:00
|
Як виглядає прапор Сирії?
|
prompter
|
uk-UA
| 3 | true | false | null | false | null | null |
e4b7d1fa-7ebe-44ca-9fdf-c604e832ccb7
|
ready_for_export
| null |
{
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0.8333333333333334,
0.25,
0.125,
0.125,
0
],
"count": [
3,
3,
2,
2,
2,
2,
3,
2,
2,
2,
2
]
}
|
893e7b06-ce92-439f-ae6c-b7fc8fb459bc
|
8fc362d7-e0b5-4f97-bfcf-b52e6f91b5d4
|
afc1303f-a5f5-4622-a2c5-b3546c7f0fe8
|
2023-02-26T16:16:03.280976+00:00
|
Як наслідок громадянської війни у Сирії, з 2012 року існує два прапори.
Прапор сирійської влади:
Горизонтально розміщені червоний-білий-чорний кольори, а також дві зелені зірки на білому кольорі.
Прапор сирійської опозиції:
Горизонтально розміщені зелений-білий-чорний кольори, а також три червоні зірки на білому кольорі.
|
assistant
|
uk-UA
| 3 | true | false | 0 | false | null | null |
e4b7d1fa-7ebe-44ca-9fdf-c604e832ccb7
|
ready_for_export
| null |
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
1,
0,
0.08333333333333333,
1,
0.4166666666666667,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
23dad9c2-5e9c-46ca-a697-738eb3220aac
|
8fc362d7-e0b5-4f97-bfcf-b52e6f91b5d4
|
ef3ad577-cbb4-4226-a17d-5a4bb8cb9b9e
|
2023-02-27T09:59:15.998343+00:00
|
Кольори прапора традиційні для прапорів арабських країн, як і на прапорах Ємену, Єгипту, Судану. Дві зірки означають Єгипет і Сирію, два народи, що ввійшли в Об'єднану Арабську Республіку. Зелений колір — колір фатімідів, білий — омейядів, чорний — аббасидів і червоний колір — кров мучеників, також червоний — колір династії Хашемитів і був доданий коли Шариф Хуссейн приєднався до Арабського повстання в 1916 році. (Wikipedia)
|
assistant
|
uk-UA
| 3 | true | false | 1 | false | null | null |
e4b7d1fa-7ebe-44ca-9fdf-c604e832ccb7
|
ready_for_export
| null |
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.5833333333333334,
0,
0.08333333333333333,
0.6666666666666666,
0.08333333333333333,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
e4bd7d22-40b4-4304-adda-1dccea55ae9c
| null |
1041538e-6836-4f45-bd4b-cb8edcd5a3fe
|
2023-02-09T17:26:55.122988+00:00
|
Hola, podrías decirme como estará el clima en los próximos 7 días en la ciudad de Lima, Perú.
|
prompter
|
es
| 4 | true | false | null | false | null |
{
"toxicity": 0.0003728418087121099,
"severe_toxicity": 0.00013407196092884988,
"obscene": 0.0013696944806724787,
"identity_attack": 0.000263629131950438,
"insult": 0.0006374709191732109,
"threat": 0.00011366624676156789,
"sexual_explicit": 0.00007726647891104221
}
|
e4bd7d22-40b4-4304-adda-1dccea55ae9c
|
ready_for_export
|
{
"name": [
"+1",
"_skip_reply",
"_skip_ranking"
],
"count": [
6,
11,
1
]
}
|
{
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0.25,
0,
0,
0.5416666666666666,
0,
0.041666666666666664,
0.4166666666666667,
0
],
"count": [
6,
4,
4,
4,
4,
4,
6,
6,
6,
6,
6
]
}
|
a26ed863-9ca5-4ef7-87d8-0b5428d412c8
|
e4bd7d22-40b4-4304-adda-1dccea55ae9c
|
81cb4b38-1f94-4bac-ba61-318c4cd08d32
|
2023-02-10T21:25:34.928854+00:00
|
Durante los primeros días de la semana se espera un tiempo nublado. La temperatura media será de 24 grados.
A mediados de semana, un frente frío se acercará a la ciudad, lo que podría traer más nubes y bajar la temperatura media a 22 grados Celsius. Sin embargo, las precipitaciones no deberían afectar significativamente a las actividades cotidianas.
Para el fin de semana, el tiempo se estabilizará y se espera una vuelta a condiciones más cálidas, aunque permanecerá parcialmente nublado con temperaturas que rondarán los 25 grados de media.
En resumen, para los próximos 7 días se esperan temperaturas frías con cielos nublados y probabilidad de lluvias en la ciudad de Lima.
|
assistant
|
es
| 3 | true | false | 0 | false | null |
{
"toxicity": 0.0003753140626940876,
"severe_toxicity": 0.00003441192893660627,
"obscene": 0.00023093765776138753,
"identity_attack": 0.00009684989345259964,
"insult": 0.0002092109789373353,
"threat": 0.000052607807447202504,
"sexual_explicit": 0.000034235174098284915
}
|
e4bd7d22-40b4-4304-adda-1dccea55ae9c
|
ready_for_export
|
{
"name": [
"+1"
],
"count": [
1
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.8333333333333334,
0.08333333333333333,
0.16666666666666666,
0.9166666666666666,
0.6666666666666666,
0.08333333333333333
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
2ce8f885-4c79-4448-b3c2-9fca76c28912
|
e4bd7d22-40b4-4304-adda-1dccea55ae9c
|
b22a9450-ef0e-4a4c-a773-01bbca83be0a
|
2023-02-10T20:17:46.923999+00:00
|
Hola, el pronóstico del clima varía constantemente por lo que te recomiendo visitar una página que tenga este detalle actualizado. Por ejemplo puedes visitar https://weather.com dónde tienes información actualizada de todo el mundo.
|
assistant
|
es
| 4 | true | false | 1 | false | null |
{
"toxicity": 0.00034594524186104536,
"severe_toxicity": 0.00230696820653975,
"obscene": 0.01622168719768524,
"identity_attack": 0.002544412622228265,
"insult": 0.013843603432178497,
"threat": 0.000983843463473022,
"sexual_explicit": 0.0005427547730505466
}
|
e4bd7d22-40b4-4304-adda-1dccea55ae9c
|
ready_for_export
|
{
"name": [
"+1",
"-1"
],
"count": [
1,
2
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0.75,
0,
0,
0,
0,
0,
0.3125,
0.25,
0.3125,
0.125,
0.25,
0.125
],
"count": [
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4
]
}
|
22bdbc4a-c30b-406d-8760-1b8bb81ea5d0
|
e4bd7d22-40b4-4304-adda-1dccea55ae9c
|
4181f5d8-4625-4ab3-adfa-c1f6ae2fede2
|
2023-02-10T20:30:02.237776+00:00
|
Claro! Aquí están 5 canciones similares a "On My Mind" de Diplo & SIDEPIECE que podrían gustarte:
"Summertime Sadness" de Lana Del Rey
"Midnight City" de M83
"Levels" de Avicii
"Fade" de Alan Walker
"Strobe" de Deadmau5
Estas canciones también tienen un tono melancólico y atmósferico, y pueden ser una buena opción para fans de "On My Mind". Espero que te gusten!
|
assistant
|
es
| 3 | true | false | 2 | false | null |
{
"toxicity": 0.0009278878569602966,
"severe_toxicity": 0.000030459064873866737,
"obscene": 0.00027032988145947456,
"identity_attack": 0.0001364011986879632,
"insult": 0.0009070296655409038,
"threat": 0.000029011334845563397,
"sexual_explicit": 0.00002795599721139297
}
|
e4bd7d22-40b4-4304-adda-1dccea55ae9c
|
ready_for_export
|
{
"name": [
"-1"
],
"count": [
1
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
1,
0,
0,
0.3333333333333333,
0,
0,
0.0625,
0.25,
0.25,
0,
0.3333333333333333,
0.16666666666666666
],
"count": [
4,
4,
3,
3,
3,
3,
3,
4,
3,
3,
3,
3,
3
]
}
|
e4c482f0-4511-4a51-b026-8d2d14360c3e
| null |
70cb8b51-8ce5-4cf3-b627-dd93a419df51
|
2023-02-12T23:30:45.222392+00:00
|
En el mundo de la programación, ¿Qué significa "MVP"?
|
prompter
|
es
| 3 | true | false | null | false | null |
{
"toxicity": 0.0003873156674671918,
"severe_toxicity": 0.00006984572246437892,
"obscene": 0.0008502552518621087,
"identity_attack": 0.00013084275997243822,
"insult": 0.0006298939697444439,
"threat": 0.00006060479790903628,
"sexual_explicit": 0.00005744678128394298
}
|
e4c482f0-4511-4a51-b026-8d2d14360c3e
|
ready_for_export
|
{
"name": [
"+1",
"_skip_reply",
"_skip_labeling"
],
"count": [
1,
1,
1
]
}
|
{
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0.8333333333333334,
0.16666666666666666,
0.3333333333333333,
0.5,
0.16666666666666666
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
342699bc-6801-4c03-a941-b94b636a71b6
|
e4c482f0-4511-4a51-b026-8d2d14360c3e
|
28e2d544-4a47-4954-a4e3-5a2660b4a660
|
2023-02-14T19:43:15.034575+00:00
|
Las siglas vienen del inglés "Minimum Viable Product" y significa "Producto Mínimo Viable" y hace referencia al producto con características suficientes para atraer a los primeros clientes y validar una idea de producto en una fase temprana del ciclo de desarrollo.
|
assistant
|
es
| 3 | true | false | 0 | false | null |
{
"toxicity": 0.00030627226806245744,
"severe_toxicity": 0.00003184592060279101,
"obscene": 0.0002457133959978819,
"identity_attack": 0.00007900276978034526,
"insult": 0.00022088711557444185,
"threat": 0.00003863902384182438,
"sexual_explicit": 0.00003085832577198744
}
|
e4c482f0-4511-4a51-b026-8d2d14360c3e
|
ready_for_export
|
{
"name": [
"+1"
],
"count": [
2
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
1,
0,
0,
1,
0.625,
0
],
"count": [
3,
2,
3,
2,
2,
2,
2,
3,
2,
2,
2,
2,
2
]
}
|
81d3fc72-1f27-4b65-9c3a-de93be5cee47
|
e4c482f0-4511-4a51-b026-8d2d14360c3e
|
f6296a77-eb11-421e-9141-42bdf991ca5f
|
2023-02-14T19:39:58.903114+00:00
|
El Producto Mínimo Viable (MVP) es un producto muy básico, con las funcionalidades esenciales y que permite probar la reacción que tiene el público objetivo. Con su feedback, es posible reconstruir y mejorar el producto, para lanzar una nueva versión y realizar el mismo proceso.
|
assistant
|
es
| 3 | true | false | 1 | false | null |
{
"toxicity": 0.00023699540179222822,
"severe_toxicity": 0.00017523436690680683,
"obscene": 0.0015452045481652021,
"identity_attack": 0.00027312675956636667,
"insult": 0.0013581545790657401,
"threat": 0.0001304068136960268,
"sexual_explicit": 0.00008395680197281763
}
|
e4c482f0-4511-4a51-b026-8d2d14360c3e
|
ready_for_export
| null |
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.75,
0,
0.25,
0.5,
0.25,
0
],
"count": [
3,
1,
3,
1,
1,
1,
1,
3,
1,
1,
1,
1,
1
]
}
|
a94f7a91-085c-41c0-b25e-542a2a195eb7
|
e4c482f0-4511-4a51-b026-8d2d14360c3e
|
0bea6f0d-d0c3-476e-886a-93c8e124ff42
|
2023-02-14T19:58:17.847715+00:00
|
En desarrollo de software y gestión de proyectos, las siglas "MVP" corresponden a la expresión inglesa "Minimum Viable Product", una técnica de desarrollo en la que un nuevo producto o web está desarrollada con las características suficientes como para satisfacer a los primeros usuarios.
|
assistant
|
es
| 3 | true | false | 2 | false | null |
{
"toxicity": 0.00028257802478037775,
"severe_toxicity": 0.00014022315735928714,
"obscene": 0.0013475578743964434,
"identity_attack": 0.0002536668907850981,
"insult": 0.0011418162612244487,
"threat": 0.00010557573841651902,
"sexual_explicit": 0.00007778649887768552
}
|
e4c482f0-4511-4a51-b026-8d2d14360c3e
|
ready_for_export
|
{
"name": [
"+1",
"_skip_labeling"
],
"count": [
1,
1
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.6666666666666666,
0,
0,
0,
0,
0
],
"count": [
3,
1,
3,
1,
1,
1,
1,
3,
1,
1,
1,
1,
1
]
}
|
e4c5240b-3427-49b3-b3c1-be6163f17cd5
| null |
3d59ead1-cd49-4ea0-bfa8-49dcf978bc3d
|
2023-02-08T23:25:44.041227+00:00
|
why the sky is blue?
|
prompter
|
en
| 3 | true | false | null | false | null |
{
"toxicity": 0.0004933023010380566,
"severe_toxicity": 0.00006408382614608854,
"obscene": 0.0007162197143770754,
"identity_attack": 0.0001525265834061429,
"insult": 0.0005857802461832762,
"threat": 0.00007099928916431963,
"sexual_explicit": 0.00005331990178092383
}
|
e4c5240b-3427-49b3-b3c1-be6163f17cd5
|
ready_for_export
|
{
"name": [
"+1",
"_skip_reply",
"_skip_ranking"
],
"count": [
2,
4,
1
]
}
|
{
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0.4375,
0.1875,
0.1875,
0.25,
0
],
"count": [
4,
3,
3,
3,
3,
3,
4,
4,
4,
4,
4
]
}
|
d1b594fc-4c2b-490c-aaad-56c306e13282
|
e4c5240b-3427-49b3-b3c1-be6163f17cd5
|
9e9664c2-a77d-4e52-978d-21cabf691987
|
2023-03-12T08:40:38.106986+00:00
|
The sky is blue because of the way that sunlight interacts with the Earth's atmosphere. Sunlight has many colors, but blue light has a shorter wavelength than other colors, so it is scattered more by the gases in the atmosphere. This scattering makes the sky appear blue to us.
|
assistant
|
en
| 3 | true | false | 0 | false | null |
{
"toxicity": 0.0005109056946821511,
"severe_toxicity": 0.00002546810355852358,
"obscene": 0.00019422482000663877,
"identity_attack": 0.00008554376108804718,
"insult": 0.00029534881468862295,
"threat": 0.00003631360232247971,
"sexual_explicit": 0.000027689553462550975
}
|
e4c5240b-3427-49b3-b3c1-be6163f17cd5
|
ready_for_export
|
{
"name": [
"+1",
"_skip_reply"
],
"count": [
2,
1
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.5,
0.08333333333333333,
0.16666666666666666,
0.5833333333333334,
0.08333333333333333,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
4b5841ff-e575-4a72-8fe0-bfa794adbfc9
|
d1b594fc-4c2b-490c-aaad-56c306e13282
|
34edfa5f-2c86-4255-9098-3d93d5df5f2f
|
2023-03-13T03:19:52.887712+00:00
|
But, if it is scattered why is it the color our eyes catch the most ?
It doesn't make sense to me, please explain me why.
|
prompter
|
en
| 3 | true | false | null | false | null |
{
"toxicity": 0.0004404569626785815,
"severe_toxicity": 0.00004271987927495502,
"obscene": 0.0003731716424226761,
"identity_attack": 0.00012513366527855396,
"insult": 0.0003556772426236421,
"threat": 0.000050398139137541875,
"sexual_explicit": 0.00003898799332091585
}
|
e4c5240b-3427-49b3-b3c1-be6163f17cd5
|
ready_for_export
|
{
"name": [
"_skip_reply"
],
"count": [
1
]
}
|
{
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0.3333333333333333,
0,
0,
0,
0,
0,
0.3333333333333333,
0,
0.125,
0.25,
0
],
"count": [
3,
3,
2,
2,
2,
2,
3,
2,
2,
2,
2
]
}
|
80711b90-76ee-4cde-a562-61cfec0a2e40
|
e4c5240b-3427-49b3-b3c1-be6163f17cd5
|
2d40e94c-40ed-4e00-a66e-454c0401c8ad
|
2023-03-12T12:02:07.243562+00:00
|
The sky appears blue to us because of the way Earth's atmosphere scatters sunlight. When the sun's light reaches the Earth's atmosphere, it is scattered in all directions by the gases and particles in the air. Blue light is scattered more than other colors because it travels as shorter, smaller waves. This is known as Rayleigh scattering.
As a result, when we look up at the sky during the daytime, we see more of the blue light scattered towards us than the other colors. This is also why sunrises and sunsets often appear to have reddish or orange hues, as during those times, the sunlight has to travel a longer distance through the Earth's atmosphere, and more of the blue light has already been scattered away, leaving behind more of the reds and oranges.
|
assistant
|
en
| 3 | true | false | 1 | false | null |
{
"toxicity": 0.0004338266735430807,
"severe_toxicity": 0.000028082840799470432,
"obscene": 0.00018764723790809512,
"identity_attack": 0.0000943776176427491,
"insult": 0.00027001844136975706,
"threat": 0.000038235240936046466,
"sexual_explicit": 0.000029307206204975955
}
|
e4c5240b-3427-49b3-b3c1-be6163f17cd5
|
ready_for_export
| null |
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.5833333333333334,
0.16666666666666666,
0,
0.6666666666666666,
0.16666666666666666,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
d6ab2a85-9524-449b-95f7-bf5defc8b2f3
|
80711b90-76ee-4cde-a562-61cfec0a2e40
|
ceab2d4d-42a0-498d-a5dc-88dbf039b403
|
2023-03-13T10:46:42.265049+00:00
|
And Is it possible to have a completely purple sky? If so, how this can be possible what in the atmosphere need to change in order to be possible.
|
prompter
|
en
| 3 | true | false | null | false | null |
{
"toxicity": 0.00029652423108927906,
"severe_toxicity": 0.00008137828262988478,
"obscene": 0.0006299023516476154,
"identity_attack": 0.000180126226041466,
"insult": 0.0005859299562871456,
"threat": 0.00007617254595970735,
"sexual_explicit": 0.000058443885791348293
}
|
e4c5240b-3427-49b3-b3c1-be6163f17cd5
|
ready_for_export
|
{
"name": [
"+1",
"_skip_reply"
],
"count": [
1,
1
]
}
|
{
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0.5833333333333334,
0.08333333333333333,
0.3333333333333333,
0.6666666666666666,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
28486e77-8150-4766-a86b-1ee58aeb356d
|
d6ab2a85-9524-449b-95f7-bf5defc8b2f3
|
2d40e94c-40ed-4e00-a66e-454c0401c8ad
|
2023-03-14T06:33:26.826801+00:00
|
It is theoretically possible for the sky to appear purple, but it would require a specific set of conditions that are not typically found in the Earth's atmosphere.
As I mentioned earlier, the color of the sky is determined by the way sunlight is scattered in the atmosphere. While blue light is scattered more than other colors, violet light is actually scattered even more than blue light. However, the human eye is not as sensitive to violet light as it is to blue light, so we see the sky as blue instead of purple.
In order for the sky to appear purple, the atmosphere would need to be selectively scattering more of the violet light towards us than the blue light. This could happen in a few different ways, such as if there were more particles in the air that preferentially scatter violet light or if the Earth's ozone layer were to change in a way that selectively filters out more blue light than violet light.
However, these conditions are not common and are not currently found in the Earth's atmosphere. Therefore, while it is theoretically possible for the sky to appear purple, it is very unlikely under normal circumstances.
|
assistant
|
en
| 3 | true | false | 0 | false | null |
{
"toxicity": 0.00040289427852258086,
"severe_toxicity": 0.00002613806827866938,
"obscene": 0.00016811199020594358,
"identity_attack": 0.0000835129976621829,
"insult": 0.00026868999702855945,
"threat": 0.00003313365232315846,
"sexual_explicit": 0.00002713295725698117
}
|
e4c5240b-3427-49b3-b3c1-be6163f17cd5
|
ready_for_export
|
{
"name": [
"+1",
"_skip_labeling"
],
"count": [
1,
2
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.6666666666666666,
0.16666666666666666,
0.16666666666666666,
0.8333333333333334,
0.4166666666666667,
0.16666666666666666
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
3d6aa109-4cf7-43e3-bafb-775c905a6e6f
|
d6ab2a85-9524-449b-95f7-bf5defc8b2f3
|
24dbdeeb-4034-4349-bde9-4eb4cbe07f4c
|
2023-03-14T05:04:22.246106+00:00
|
It is not possible to have a completely purple sky. The colors we see in the sky are due to the scattering of sunlight by the Earth's atmosphere, which separates the different colors of light. The colors we typically see in the sky are blue and orange/red during sunrise and sunset.
To have a completely purple sky, the atmosphere would need to scatter light differently. One possible way this could happen is if the Earth's atmosphere contained more atmospheric particles that scatter shorter-wavelength light, such as violet and blue. However, this would also affect the way we perceive other colors in our environment, and could have significant impacts on human health and well-being. So while a purple sky may be theoretically possible, it is not likely to occur in the natural world as we know it.
|
assistant
|
en
| 3 | true | false | 1 | false | null |
{
"toxicity": 0.00035488230059854686,
"severe_toxicity": 0.00003357904643053189,
"obscene": 0.00021143753838259727,
"identity_attack": 0.00010126069537363946,
"insult": 0.0002800512302201241,
"threat": 0.00003942381954402663,
"sexual_explicit": 0.00003313759953016415
}
|
e4c5240b-3427-49b3-b3c1-be6163f17cd5
|
ready_for_export
|
{
"name": [
"_skip_labeling"
],
"count": [
1
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.75,
0,
0.5,
0.75,
0.6666666666666666,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
91124a32-402a-4ba7-9c8f-2d24ca8ee7ff
|
e4c5240b-3427-49b3-b3c1-be6163f17cd5
|
a267bd78-d757-4bc4-949d-c8ce1e8fb66a
|
2023-03-12T10:15:41.212412+00:00
|
The sky appears blue to us because of a phenomenon known as Rayleigh scattering. As sunlight enters the Earth's atmosphere, it encounters tiny gas molecules, such as nitrogen and oxygen. These gas molecules scatter the sunlight in all directions.
However, blue light is scattered more than other colors of light because it travels in shorter, smaller waves. This means that more of the blue light is redirected in different directions, causing the sky to appear blue to us from our vantage point on the ground.
At sunset or sunrise, the sun's light has to pass through more of the Earth's atmosphere to reach us. During this time, the other colors of light are scattered and only the longer wavelengths of red and orange are left to reach us, creating the beautiful red and orange hues that we associate with sunsets and sunrises.
|
assistant
|
en
| 3 | true | false | 2 | false | null |
{
"toxicity": 0.0004087121633347124,
"severe_toxicity": 0.000026795154553838074,
"obscene": 0.0001768332876963541,
"identity_attack": 0.00008938179962569848,
"insult": 0.0002491852210368961,
"threat": 0.00003731174729182385,
"sexual_explicit": 0.000027236603273195215
}
|
e4c5240b-3427-49b3-b3c1-be6163f17cd5
|
ready_for_export
|
{
"name": [
"+1"
],
"count": [
1
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.16666666666666666,
0.16666666666666666,
0.16666666666666666,
0.25,
0.16666666666666666,
0.16666666666666666
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
1ef157a8-aee3-4d1c-8f68-92eef549b3a3
|
91124a32-402a-4ba7-9c8f-2d24ca8ee7ff
|
29ed3580-e40c-419a-9712-b121bb51295b
|
2023-03-13T00:16:52.911952+00:00
|
Simplify this explanation unless specifically asked for this amount of detail.
|
prompter
|
en
| 3 | true | false | null | false | null |
{
"toxicity": 0.0005458975792862475,
"severe_toxicity": 0.000033540611184434965,
"obscene": 0.00023987868917174637,
"identity_attack": 0.00012058488937327638,
"insult": 0.0003541882324498147,
"threat": 0.00004768646613229066,
"sexual_explicit": 0.00002721386044868268
}
|
e4c5240b-3427-49b3-b3c1-be6163f17cd5
|
ready_for_export
|
{
"name": [
"+1",
"_skip_reply"
],
"count": [
1,
4
]
}
|
{
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0.4166666666666667,
0.25,
0.25,
0.25,
0
],
"count": [
3,
3,
1,
1,
1,
1,
3,
1,
1,
1,
1
]
}
|
1c04181a-d21d-43e4-9b3a-53b1718bb624
|
1ef157a8-aee3-4d1c-8f68-92eef549b3a3
|
1aaa9be1-0d07-4cb2-a2d7-4301cbfc4ecc
|
2023-03-13T20:23:38.885365+00:00
|
The sky appears blue because when sunlight enters the Earth's atmosphere, the gas molecules scatter the blue light more than other colors, causing it to reach our eyes from all directions and making the sky appear blue. During sunset and sunrise, the other colors are scattered and only the red and orange hues are left to reach us, creating the beautiful colors we see.
|
assistant
|
en
| 3 | true | false | 0 | false | null |
{
"toxicity": 0.00042148728971369565,
"severe_toxicity": 0.00003896639827871695,
"obscene": 0.0002633635886013508,
"identity_attack": 0.00011765199451474473,
"insult": 0.00030501955188810825,
"threat": 0.000046109100367175415,
"sexual_explicit": 0.000043038013245677575
}
|
e4c5240b-3427-49b3-b3c1-be6163f17cd5
|
ready_for_export
|
{
"name": [
"_skip_labeling"
],
"count": [
1
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.6666666666666666,
0,
0.16666666666666666,
0.75,
0.4166666666666667,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
59100785-bc6c-415b-9564-9b601b8c5419
|
1c04181a-d21d-43e4-9b3a-53b1718bb624
|
670f282c-2df8-4b06-a6c2-449038f729f6
|
2023-03-14T04:43:18.435132+00:00
|
Explain further please.
|
prompter
|
en
| 3 | true | false | null | false | null |
{
"toxicity": 0.0002925388398580253,
"severe_toxicity": 0.00015189927944447845,
"obscene": 0.0011682710610330105,
"identity_attack": 0.0002791901642922312,
"insult": 0.0009671725565567613,
"threat": 0.00013720318384002894,
"sexual_explicit": 0.00008476778748445213
}
|
e4c5240b-3427-49b3-b3c1-be6163f17cd5
|
ready_for_export
| null |
{
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0.5833333333333334,
0.16666666666666666,
0,
0,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
87b8b0cb-49b6-4ac4-933b-480a8e75ddb6
|
1ef157a8-aee3-4d1c-8f68-92eef549b3a3
|
7859b9ff-4cd8-463d-8b6f-0d0181fbbc4f
|
2023-03-14T12:55:03.534509+00:00
|
Got you! The sky is blue because the atmosphere acts as a filter, blocking, absorbing, and reflecting most other colors except for blue, which can your retina.
|
assistant
|
en
| 3 | true | false | 1 | false | null |
{
"toxicity": 0.002237694337964058,
"severe_toxicity": 0.000017247124560526572,
"obscene": 0.00018505255866330117,
"identity_attack": 0.00008932300988817587,
"insult": 0.0010165161220356822,
"threat": 0.00003365836528246291,
"sexual_explicit": 0.00003602290962589905
}
|
e4c5240b-3427-49b3-b3c1-be6163f17cd5
|
ready_for_export
|
{
"name": [
"-1",
"red_flag",
"_skip_labeling"
],
"count": [
1,
1,
1
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0.6666666666666666,
0,
0,
0,
0,
0,
0.3333333333333333,
0,
0,
0.6666666666666666,
0.08333333333333333,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
0b8e4d3b-fb4a-4b5b-b47a-cd56a9526d2c
|
1ef157a8-aee3-4d1c-8f68-92eef549b3a3
|
39686f6c-edba-4558-84e6-9834931b899c
|
2023-03-14T02:37:52.815766+00:00
|
I like turtles
|
assistant
|
en
| 3 | false | true | null | false | null |
{
"toxicity": 0.0009980025934055448,
"severe_toxicity": 0.000010692408977774903,
"obscene": 0.00007893695874372497,
"identity_attack": 0.00008118682308122516,
"insult": 0.00044094640179537237,
"threat": 0.000023387618057313375,
"sexual_explicit": 0.000018196280507254414
}
|
e4c5240b-3427-49b3-b3c1-be6163f17cd5
|
ready_for_export
|
{
"name": [
"-1",
"red_flag"
],
"count": [
3,
1
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0.6666666666666666,
0.6666666666666666,
0,
0,
0.3333333333333333,
0,
0,
0.16666666666666666,
0.08333333333333333,
0.6666666666666666,
0,
0.3333333333333333,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
e4f8859c-5f3f-4685-9b5f-77ec526cdefc
| null |
d84e29e8-1a3a-4093-b210-4f7a0d95bb49
|
2023-01-18T17:24:45.682351+00:00
|
Tell me a knock-knock joke.
|
prompter
|
en
| 3 | true | false | null | false | null |
{
"toxicity": 0.0464816614985466,
"severe_toxicity": 0.000163525968673639,
"obscene": 0.0022105679381638765,
"identity_attack": 0.00020445467089302838,
"insult": 0.005757644306868315,
"threat": 0.019289977848529816,
"sexual_explicit": 0.0007197909289970994
}
|
e4f8859c-5f3f-4685-9b5f-77ec526cdefc
|
ready_for_export
| null |
{
"name": [
"spam",
"fails_task",
"not_appropriate",
"hate_speech",
"sexual_content",
"moral_judgement",
"political_content",
"toxicity",
"humor",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0,
0.94,
0
],
"count": [
3,
1,
1,
1,
1,
1,
1,
1,
1,
1
]
}
|
accfad83-62ca-41fe-b17e-cd32ff113be2
|
e4f8859c-5f3f-4685-9b5f-77ec526cdefc
|
903a7cca-4e1c-4e48-9fea-3ee30215f3c6
|
2023-01-18T17:46:01.943334+00:00
|
Knock knock!
|
assistant
|
en
| 3 | true | false | 0 | false | null |
{
"toxicity": 0.1206696555018425,
"severe_toxicity": 0.000279893254628405,
"obscene": 0.0011540551204234362,
"identity_attack": 0.0005647072684951127,
"insult": 0.0037525855004787445,
"threat": 0.10315212607383728,
"sexual_explicit": 0.0007511750445701182
}
|
e4f8859c-5f3f-4685-9b5f-77ec526cdefc
|
ready_for_export
| null |
{
"name": [
"spam"
],
"value": [
0
],
"count": [
3
]
}
|
7640a4bc-c7f1-4bb7-be9c-b841ac952d42
|
accfad83-62ca-41fe-b17e-cd32ff113be2
|
ca4bc50c-8ac0-403a-8545-a228af08227d
|
2023-01-18T18:43:47.592957+00:00
|
Who is there?
|
prompter
|
en
| 3 | true | false | null | false | null |
{
"toxicity": 0.0005200635059736669,
"severe_toxicity": 0.000022191026801010594,
"obscene": 0.00015133386477828026,
"identity_attack": 0.00009030741784954444,
"insult": 0.00024264914100058377,
"threat": 0.00003875504989991896,
"sexual_explicit": 0.00002340819082746748
}
|
e4f8859c-5f3f-4685-9b5f-77ec526cdefc
|
ready_for_export
| null |
{
"name": [
"spam"
],
"value": [
0
],
"count": [
3
]
}
|
bc7e59c7-3f61-4600-87e8-fb3f6a98a828
|
accfad83-62ca-41fe-b17e-cd32ff113be2
|
d84e29e8-1a3a-4093-b210-4f7a0d95bb49
|
2023-01-23T04:14:59.079596+00:00
|
Who's there?
|
prompter
|
en
| 3 | true | false | null | false | null |
{
"toxicity": 0.0005208674701862037,
"severe_toxicity": 0.00001948351382452529,
"obscene": 0.00012769000022672117,
"identity_attack": 0.00008957190584624186,
"insult": 0.00020317206508480012,
"threat": 0.000036378281947690994,
"sexual_explicit": 0.0000216558273677947
}
|
e4f8859c-5f3f-4685-9b5f-77ec526cdefc
|
ready_for_export
| null |
{
"name": [
"spam"
],
"value": [
0
],
"count": [
3
]
}
|
d04c0655-0a7d-457c-84f8-a8212d11050f
|
accfad83-62ca-41fe-b17e-cd32ff113be2
|
01e6aede-02f9-4d4f-9d85-7b5544a36b78
|
2023-01-18T20:07:37.695956+00:00
|
Who's there?
|
prompter
|
en
| 4 | true | false | null | false | null |
{
"toxicity": 0.0005208674701862037,
"severe_toxicity": 0.00001948351382452529,
"obscene": 0.00012769000022672117,
"identity_attack": 0.00008957190584624186,
"insult": 0.00020317206508480012,
"threat": 0.000036378281947690994,
"sexual_explicit": 0.0000216558273677947
}
|
e4f8859c-5f3f-4685-9b5f-77ec526cdefc
|
ready_for_export
| null |
{
"name": [
"spam"
],
"value": [
0
],
"count": [
4
]
}
|
c868587b-9cd6-4cc8-ab62-be6bbb4f9309
|
d04c0655-0a7d-457c-84f8-a8212d11050f
|
2c22bbc2-0731-4189-a149-b17b43f795af
|
2023-01-25T10:07:20.368004+00:00
|
Boo.
|
assistant
|
en
| 3 | true | false | 0 | false | null |
{
"toxicity": 0.0030326854903250933,
"severe_toxicity": 0.0000341064587701112,
"obscene": 0.0004383187915664166,
"identity_attack": 0.00012772483751177788,
"insult": 0.001448142807930708,
"threat": 0.00012286845594644547,
"sexual_explicit": 0.00006135927833383903
}
|
e4f8859c-5f3f-4685-9b5f-77ec526cdefc
|
ready_for_export
| null |
{
"name": [
"spam"
],
"value": [
0.25
],
"count": [
3
]
}
|
024a9b47-0389-4d68-9322-8a5c1c2e1c16
|
d04c0655-0a7d-457c-84f8-a8212d11050f
|
d84e29e8-1a3a-4093-b210-4f7a0d95bb49
|
2023-01-23T03:53:02.110627+00:00
|
Dejav.
|
assistant
|
en
| 3 | true | false | 1 | false | null |
{
"toxicity": 0.0019859380554407835,
"severe_toxicity": 0.00005984596282360144,
"obscene": 0.0006760776741430163,
"identity_attack": 0.00020132890495005995,
"insult": 0.0015263566747307777,
"threat": 0.00021379334793891758,
"sexual_explicit": 0.00007164637645473704
}
|
e4f8859c-5f3f-4685-9b5f-77ec526cdefc
|
ready_for_export
| null |
{
"name": [
"spam",
"fails_task",
"not_appropriate",
"hate_speech",
"sexual_content",
"moral_judgement",
"political_content",
"toxicity",
"humor",
"violence"
],
"value": [
0,
0,
0.25,
0,
0,
0,
0.5,
0.25,
1,
0
],
"count": [
3,
1,
1,
1,
1,
1,
1,
1,
1,
1
]
}
|
86c96e87-7b6f-4b0c-8372-d4d0acfb0f35
|
d04c0655-0a7d-457c-84f8-a8212d11050f
|
d84e29e8-1a3a-4093-b210-4f7a0d95bb49
|
2023-01-24T23:57:18.358551+00:00
|
Open Assistant.
|
assistant
|
en
| 3 | true | false | 2 | false | null |
{
"toxicity": 0.0002913414500653744,
"severe_toxicity": 0.000035521512472769246,
"obscene": 0.00020305259386077523,
"identity_attack": 0.0001052984589478001,
"insult": 0.0002607548958621919,
"threat": 0.00005209410301176831,
"sexual_explicit": 0.000030451075872406363
}
|
e4f8859c-5f3f-4685-9b5f-77ec526cdefc
|
ready_for_export
| null |
{
"name": [
"spam"
],
"value": [
0
],
"count": [
3
]
}
|
7bce75c8-ce8c-45e5-8308-653ea3025650
|
d04c0655-0a7d-457c-84f8-a8212d11050f
|
d84e29e8-1a3a-4093-b210-4f7a0d95bb49
|
2023-01-20T00:43:29.072631+00:00
|
Nana.
|
assistant
|
en
| 3 | true | false | 3 | false | null |
{
"toxicity": 0.005673584528267384,
"severe_toxicity": 0.000027781705284724012,
"obscene": 0.0005094152875244617,
"identity_attack": 0.00013321508595254272,
"insult": 0.0037793326191604137,
"threat": 0.00008413969771936536,
"sexual_explicit": 0.000055515287385787815
}
|
e4f8859c-5f3f-4685-9b5f-77ec526cdefc
|
ready_for_export
| null |
{
"name": [
"spam"
],
"value": [
0
],
"count": [
3
]
}
|
8f086979-7c14-4043-a19f-e3cc22f10666
|
d04c0655-0a7d-457c-84f8-a8212d11050f
|
ca4bc50c-8ac0-403a-8545-a228af08227d
|
2023-01-18T20:54:56.735489+00:00
|
WHO WHO WHO
|
assistant
|
en
| 3 | true | false | 4 | false | null |
{
"toxicity": 0.00028973844018764794,
"severe_toxicity": 0.0003392779908608645,
"obscene": 0.002599026309326291,
"identity_attack": 0.0003949619713239372,
"insult": 0.0017521323170512915,
"threat": 0.00021669130364898592,
"sexual_explicit": 0.00015363855345640332
}
|
e4f8859c-5f3f-4685-9b5f-77ec526cdefc
|
ready_for_export
| null |
{
"name": [
"spam"
],
"value": [
0
],
"count": [
3
]
}
|
dc442998-c4e1-4043-9854-8e8df1a7b41e
|
accfad83-62ca-41fe-b17e-cd32ff113be2
|
ca4bc50c-8ac0-403a-8545-a228af08227d
|
2023-01-18T19:41:36.561373+00:00
|
Nvm
|
prompter
|
en
| 3 | true | false | null | false | null |
{
"toxicity": 0.0004654536896850914,
"severe_toxicity": 0.00003389078119653277,
"obscene": 0.00023297920415643603,
"identity_attack": 0.00012335774954408407,
"insult": 0.0002614646218717098,
"threat": 0.00006209553976077586,
"sexual_explicit": 0.00002730479354795534
}
|
e4f8859c-5f3f-4685-9b5f-77ec526cdefc
|
ready_for_export
| null |
{
"name": [
"spam"
],
"value": [
0
],
"count": [
3
]
}
|
8ec0f77d-96e7-443b-bdbd-b1f5a493a821
|
dc442998-c4e1-4043-9854-8e8df1a7b41e
|
d84e29e8-1a3a-4093-b210-4f7a0d95bb49
|
2023-01-18T19:47:47.902853+00:00
|
Understood. Is there anything else I can help you with?
|
assistant
|
en
| 3 | true | false | 0 | false | null |
{
"toxicity": 0.0005794167518615723,
"severe_toxicity": 0.000043414158426458016,
"obscene": 0.0003008460043929517,
"identity_attack": 0.0001459063932998106,
"insult": 0.0003664593677967787,
"threat": 0.00006030657823430374,
"sexual_explicit": 0.000026387922844151035
}
|
e4f8859c-5f3f-4685-9b5f-77ec526cdefc
|
ready_for_export
| null |
{
"name": [
"spam"
],
"value": [
0
],
"count": [
3
]
}
|
8291b059-6d1d-4267-924d-0d05f316f0ad
|
dc442998-c4e1-4043-9854-8e8df1a7b41e
|
ca4bc50c-8ac0-403a-8545-a228af08227d
|
2023-01-18T20:46:47.190363+00:00
|
Understood. Is there anything else I might help you with?
|
assistant
|
en
| 3 | true | false | 1 | false | null |
{
"toxicity": 0.0005318816984072328,
"severe_toxicity": 0.000049127687816508114,
"obscene": 0.0003322778211440891,
"identity_attack": 0.00015121903561521322,
"insult": 0.00039580173324793577,
"threat": 0.00006637043406954035,
"sexual_explicit": 0.000028924618163728155
}
|
e4f8859c-5f3f-4685-9b5f-77ec526cdefc
|
ready_for_export
| null |
{
"name": [
"spam"
],
"value": [
0
],
"count": [
3
]
}
|
a4ee8db5-7a3f-43c7-9713-b20655a6619b
|
dc442998-c4e1-4043-9854-8e8df1a7b41e
|
6af41497-d003-4da1-b2bf-d4494a6f763f
|
2023-01-22T19:16:33.693318+00:00
|
Is there anything else that I can help you with today?
|
assistant
|
en
| 3 | true | false | 2 | false | null |
{
"toxicity": 0.0006041068118065596,
"severe_toxicity": 0.00002697357012948487,
"obscene": 0.00015393359353765845,
"identity_attack": 0.0001417691382812336,
"insult": 0.00021068486967124045,
"threat": 0.00005331253123586066,
"sexual_explicit": 0.000020985777155146934
}
|
e4f8859c-5f3f-4685-9b5f-77ec526cdefc
|
ready_for_export
| null |
{
"name": [
"spam",
"fails_task",
"not_appropriate",
"hate_speech",
"sexual_content",
"moral_judgement",
"political_content",
"toxicity",
"humor",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0,
0,
0
],
"count": [
3,
1,
1,
1,
1,
1,
1,
1,
1,
1
]
}
|
814d69ad-0d4b-4bb5-83d1-2a47e6aecb2a
|
e4f8859c-5f3f-4685-9b5f-77ec526cdefc
|
d84e29e8-1a3a-4093-b210-4f7a0d95bb49
|
2023-01-18T22:00:46.735179+00:00
|
Knock knock...
|
assistant
|
en
| 3 | true | false | 1 | false | null |
{
"toxicity": 0.07072703540325165,
"severe_toxicity": 0.0001795096613932401,
"obscene": 0.0007977715576998889,
"identity_attack": 0.00041039270581677556,
"insult": 0.003615116700530052,
"threat": 0.05344698578119278,
"sexual_explicit": 0.000488501857034862
}
|
e4f8859c-5f3f-4685-9b5f-77ec526cdefc
|
ready_for_export
| null |
{
"name": [
"spam"
],
"value": [
0
],
"count": [
3
]
}
|
2fa738f8-287f-420f-9134-1c4fc61b5d4e
|
814d69ad-0d4b-4bb5-83d1-2a47e6aecb2a
|
c6fe755f-14b8-457e-a7d3-1d766cd36881
|
2023-01-21T16:51:29.549293+00:00
|
Who's there? That's not a joke!
|
prompter
|
en
| 3 | true | false | null | false | null |
{
"toxicity": 0.0006949813687242568,
"severe_toxicity": 0.000021443251171149313,
"obscene": 0.00019510311540216208,
"identity_attack": 0.00008549360791221261,
"insult": 0.0002651286486070603,
"threat": 0.00004153858753852546,
"sexual_explicit": 0.00003033536995644681
}
|
e4f8859c-5f3f-4685-9b5f-77ec526cdefc
|
ready_for_export
| null |
{
"name": [
"spam"
],
"value": [
0
],
"count": [
3
]
}
|
7514a763-5f03-4ed5-b029-055f9fb32321
|
2fa738f8-287f-420f-9134-1c4fc61b5d4e
|
d84e29e8-1a3a-4093-b210-4f7a0d95bb49
|
2023-01-25T03:44:00.240379+00:00
|
Chickens. (Be patient!)
|
assistant
|
en
| 3 | true | false | null | false | null |
{
"toxicity": 0.013051558285951614,
"severe_toxicity": 0.00011309701221762225,
"obscene": 0.0029961587861180305,
"identity_attack": 0.0003048773796763271,
"insult": 0.005809418857097626,
"threat": 0.0011318317847326398,
"sexual_explicit": 0.0013126000994816422
}
|
e4f8859c-5f3f-4685-9b5f-77ec526cdefc
|
ready_for_export
| null |
{
"name": [
"spam"
],
"value": [
0
],
"count": [
3
]
}
|
e4f938eb-322a-4672-94c0-b597d1930822
| null |
885f7c99-889f-430c-ab5a-16a25ce6993e
|
2023-02-04T22:00:32.171887+00:00
|
xpath to get a span node that contains the text " Estimate ".
HTML
<span class="">
Estimate
<span class="font-dark-d floatRight">25 - 35 EUR</span>
</span>
|
prompter
|
en
| 4 | true | false | null | false | null |
{
"toxicity": 0.00034265517024323344,
"severe_toxicity": 0.00003444883259362541,
"obscene": 0.00015837278624530882,
"identity_attack": 0.00014066629228182137,
"insult": 0.0001688010961515829,
"threat": 0.0000404084894398693,
"sexual_explicit": 0.000026674279069993645
}
|
e4f938eb-322a-4672-94c0-b597d1930822
|
ready_for_export
|
{
"name": [
"+1",
"-1",
"_skip_reply",
"_skip_ranking",
"_skip_labeling"
],
"count": [
2,
16,
9,
4,
1
]
}
|
{
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0.4375,
0.125,
0,
0.3125,
0
],
"count": [
4,
4,
4,
4,
4,
4,
4,
4,
4,
4,
4
]
}
|
0039af9d-fd8e-44f7-8e1b-0c667b4b6497
|
e4f938eb-322a-4672-94c0-b597d1930822
|
ecaa4818-48da-45a8-bab5-ae6de585ad8a
|
2023-02-05T10:23:11.253385+00:00
|
Here's an example of an XPath expression to select the span node that contains the text "Estimate":
//span[normalize-space(text())="Estimate"]
This selects any "span" element that has normalized text content of "Estimate".
|
assistant
|
en
| 3 | true | false | 0 | false | null |
{
"toxicity": 0.00041137446532957256,
"severe_toxicity": 0.000024406399461440742,
"obscene": 0.00010410417598905042,
"identity_attack": 0.00011530979827512056,
"insult": 0.0001381780457450077,
"threat": 0.000034970755223184824,
"sexual_explicit": 0.000022652189727523364
}
|
e4f938eb-322a-4672-94c0-b597d1930822
|
ready_for_export
|
{
"name": [
"_skip_reply",
"_skip_labeling"
],
"count": [
7,
1
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.8333333333333334,
0.08333333333333333,
0.4166666666666667,
1,
0.5833333333333334,
0.16666666666666666
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
766394bb-0bd0-456c-b0e2-34effb77309e
|
0039af9d-fd8e-44f7-8e1b-0c667b4b6497
|
fa18fc57-256f-41b0-b700-679648cf9792
|
2023-02-05T13:01:45.575697+00:00
|
perfect
|
prompter
|
en
| 3 | true | false | null | false | null |
{
"toxicity": 0.0004600746906362474,
"severe_toxicity": 0.000023779459297657013,
"obscene": 0.00015376856026705354,
"identity_attack": 0.00011286257358733565,
"insult": 0.0002053463103948161,
"threat": 0.00004556702697300352,
"sexual_explicit": 0.00002475442670402117
}
|
e4f938eb-322a-4672-94c0-b597d1930822
|
ready_for_export
|
{
"name": [
"-1",
"_skip_labeling"
],
"count": [
1,
1
]
}
|
{
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0.25,
0.08333333333333333,
0.08333333333333333,
0,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
03b37c6a-f5a0-4874-8bc7-d01ff55f749a
|
e4f938eb-322a-4672-94c0-b597d1930822
|
8e2cc853-0e4a-4d64-8765-2505aa5dd97c
|
2023-02-05T10:35:21.274303+00:00
|
Your node contains the text "Estimate" at it's root. To get your root node via XPath simply use the wildcard to select the root node:
/*
|
assistant
|
en
| 3 | true | false | 1 | false | null |
{
"toxicity": 0.0003634289023466408,
"severe_toxicity": 0.00003284629201516509,
"obscene": 0.0001660580892348662,
"identity_attack": 0.00011765312956413254,
"insult": 0.00018970620294567198,
"threat": 0.000043647291022352874,
"sexual_explicit": 0.000028451877369661815
}
|
e4f938eb-322a-4672-94c0-b597d1930822
|
ready_for_export
|
{
"name": [
"-1",
"_skip_labeling"
],
"count": [
3,
9
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.25,
0.25,
0.08333333333333333,
0.16666666666666666,
0.08333333333333333,
0.08333333333333333
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
8cbef442-4198-405c-b759-f7a6780479e0
|
03b37c6a-f5a0-4874-8bc7-d01ff55f749a
|
18a0b35e-ff29-4474-9cc1-1dc13ea39373
|
2023-02-05T15:13:05.745446+00:00
|
can you provide the the code so that it works?
|
prompter
|
en
| 3 | true | false | null | false | null |
{
"toxicity": 0.00040405799518339336,
"severe_toxicity": 0.00004754924157168716,
"obscene": 0.00033642686321400106,
"identity_attack": 0.00015873229131102562,
"insult": 0.0002983919985126704,
"threat": 0.0000649154681013897,
"sexual_explicit": 0.00003935590575565584
}
|
e4f938eb-322a-4672-94c0-b597d1930822
|
ready_for_export
|
{
"name": [
"_skip_labeling"
],
"count": [
1
]
}
|
{
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0.75,
0,
0,
0,
0
],
"count": [
3,
3,
2,
2,
2,
2,
3,
2,
2,
2,
2
]
}
|
fc3a3cb6-1b19-448c-87a6-a489ac68dc93
|
03b37c6a-f5a0-4874-8bc7-d01ff55f749a
|
57e36f72-719d-4ace-938a-0ab38effdaea
|
2023-02-05T15:13:28.548278+00:00
|
Your response is missing the code snippet.
|
prompter
|
en
| 3 | true | false | null | false | null |
{
"toxicity": 0.0019145391415804625,
"severe_toxicity": 0.000017766958990250714,
"obscene": 0.00015423257718794048,
"identity_attack": 0.00011129264021292329,
"insult": 0.0009578298777341843,
"threat": 0.0000399303826270625,
"sexual_explicit": 0.000020109508113819174
}
|
e4f938eb-322a-4672-94c0-b597d1930822
|
ready_for_export
|
{
"name": [
"_skip_labeling"
],
"count": [
3
]
}
|
{
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0.3333333333333333,
0,
0,
0.3333333333333333,
0.3333333333333333,
0.08333333333333333,
0.08333333333333333,
0.16666666666666666
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
c06e31b5-ef92-4e6a-ba1a-c89a7f9773b0
|
e4f938eb-322a-4672-94c0-b597d1930822
|
336fbad0-0d82-4903-9a73-d38daafbb0a2
|
2023-02-05T10:30:30.860515+00:00
|
Can you be more specific with your question?
|
assistant
|
en
| 3 | true | false | 2 | false | null |
{
"toxicity": 0.0006822716095484793,
"severe_toxicity": 0.000022072938008932397,
"obscene": 0.0001827784872148186,
"identity_attack": 0.00009099708404392004,
"insult": 0.00031908220262266695,
"threat": 0.000034832592064049095,
"sexual_explicit": 0.000025757102775969543
}
|
e4f938eb-322a-4672-94c0-b597d1930822
|
ready_for_export
|
{
"name": [
"+1",
"-1",
"_skip_reply",
"_skip_labeling"
],
"count": [
1,
10,
2,
1
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0.3333333333333333,
0.3333333333333333,
0,
0,
0,
0,
0,
0.25,
0.4166666666666667,
0,
0.16666666666666666,
0.16666666666666666,
0.08333333333333333
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
6be92bb1-4e0f-4096-974d-a06358fc7b2b
|
c06e31b5-ef92-4e6a-ba1a-c89a7f9773b0
|
86b60e64-4732-47e1-aa47-446b4cdf53d4
|
2023-02-05T12:31:02.815240+00:00
|
I'm looking for the xPath I can use in my javascript to refer to that HTML element.
|
prompter
|
en
| 3 | true | false | null | false | null |
{
"toxicity": 0.0003503990010358393,
"severe_toxicity": 0.000027534875698620453,
"obscene": 0.00011350474960636348,
"identity_attack": 0.00013115441834088415,
"insult": 0.00013305018364917487,
"threat": 0.0000413952766393777,
"sexual_explicit": 0.00002869624768209178
}
|
e4f938eb-322a-4672-94c0-b597d1930822
|
ready_for_export
|
{
"name": [
"+1",
"_skip_reply",
"_skip_ranking"
],
"count": [
6,
5,
6
]
}
|
{
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0.5833333333333334,
0.125,
0.125,
0.375,
0
],
"count": [
3,
3,
2,
2,
2,
2,
3,
2,
2,
2,
2
]
}
|
9bb87cdd-c939-4c5d-8257-48b51e2af68c
|
6be92bb1-4e0f-4096-974d-a06358fc7b2b
|
57e36f72-719d-4ace-938a-0ab38effdaea
|
2023-02-05T15:01:45.317470+00:00
|
The XPath expression to use would be `//span[contains(text(), ' Estimate ')]`.
You can fetch all matching elements in JavaScript using the following snippet:
```js
// Iterator over all span elements that contain ' Estimate '.
const iterator = document.evaluate("//span[contains(text(), ' Estimate ')]", document, null, XPathResult.UNORDERED_NODE_ITERATOR_TYPE, null);
```
|
assistant
|
en
| 3 | true | false | 0 | false | null |
{
"toxicity": 0.000252850994002074,
"severe_toxicity": 0.000033209158573299646,
"obscene": 0.00011459904635557905,
"identity_attack": 0.00012145360233262181,
"insult": 0.00012370453623589128,
"threat": 0.00003972255581174977,
"sexual_explicit": 0.000025755582100828178
}
|
e4f938eb-322a-4672-94c0-b597d1930822
|
ready_for_export
|
{
"name": [
"+1",
"_skip_labeling"
],
"count": [
1,
1
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.75,
0.08333333333333333,
0.08333333333333333,
0.9166666666666666,
0.16666666666666666,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
8b7ff845-bec3-46e3-9894-1f3d4542fdd0
|
6be92bb1-4e0f-4096-974d-a06358fc7b2b
|
a851134e-ac01-4304-b59f-76f7371439e0
|
2023-02-05T14:53:28.272251+00:00
|
The xpath expression to select the span node that contains the text "Estimate" would be:
//span[text()='Estimate']
|
assistant
|
en
| 3 | true | false | 1 | false | null |
{
"toxicity": 0.0003998994652647525,
"severe_toxicity": 0.000036644396459450945,
"obscene": 0.0001497390039730817,
"identity_attack": 0.0001976111379917711,
"insult": 0.00016594206681475043,
"threat": 0.00004662097126129083,
"sexual_explicit": 0.00002872962795663625
}
|
e4f938eb-322a-4672-94c0-b597d1930822
|
ready_for_export
|
{
"name": [
"_skip_labeling"
],
"count": [
1
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.9166666666666666,
0.08333333333333333,
0.16666666666666666,
0.9166666666666666,
0.4166666666666667,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
146cd68f-ffc6-4c49-acb9-0becc29ae0d9
|
6be92bb1-4e0f-4096-974d-a06358fc7b2b
|
2ea4d2e3-dfae-4a4d-a1ea-64b7e529b745
|
2023-02-05T14:55:50.323642+00:00
|
//span[normalize-space(text())='Estimate']
|
assistant
|
en
| 3 | true | false | 2 | false | null |
{
"toxicity": 0.00024287479755003005,
"severe_toxicity": 0.0000922229592106305,
"obscene": 0.00036177190486341715,
"identity_attack": 0.00027227657847106457,
"insult": 0.00038188573671504855,
"threat": 0.00010307892080163583,
"sexual_explicit": 0.00004305730544729158
}
|
e4f938eb-322a-4672-94c0-b597d1930822
|
ready_for_export
| null |
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.25,
0.16666666666666666,
0.16666666666666666,
0.25,
0.16666666666666666,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
ed88b24e-9c5e-4f59-bbbf-15e78e4c21e3
|
6be92bb1-4e0f-4096-974d-a06358fc7b2b
|
12ba2780-6069-4d0c-a833-d216e1f6997b
|
2023-02-05T15:04:13.013028+00:00
|
I think that would be `/span::text()`.
|
assistant
|
en
| 3 | true | false | 3 | false | null |
{
"toxicity": 0.000472329615149647,
"severe_toxicity": 0.000026366942620370537,
"obscene": 0.00008865602285368368,
"identity_attack": 0.00015718770737294108,
"insult": 0.00014251960965339094,
"threat": 0.0000394389389839489,
"sexual_explicit": 0.000023940627215779386
}
|
e4f938eb-322a-4672-94c0-b597d1930822
|
ready_for_export
|
{
"name": [
"-1",
"_skip_labeling"
],
"count": [
2,
2
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0.6666666666666666,
0,
0,
0,
0,
0,
0.25,
0.3333333333333333,
0,
0.4166666666666667,
0.16666666666666666,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
e4fa33ba-fd13-4c22-b1a0-30e3199f4f60
| null |
b2b4511f-94f0-4d57-8128-305482de3baa
|
2023-02-18T01:02:16.841917+00:00
|
Write a non-rhyming poem with strong alliteration and where every other line favors words that start with vowels or consonants in the combined style of Mark Strand and Elizabeth Bishop about a man who was injured in an accident and is wandering around in a state of shock while seeking help but seems to be invisible to everyone he approaches until he finally realized he didn't survive the accident and is in fact a ghost
|
prompter
|
en
| 3 | true | false | null | false | null |
{
"toxicity": 0.0017092638881877065,
"severe_toxicity": 0.00008965847518993542,
"obscene": 0.0004080367216374725,
"identity_attack": 0.00021513804676942527,
"insult": 0.0012700719526037574,
"threat": 0.0000982680285233073,
"sexual_explicit": 0.00013535907783079892
}
|
e4fa33ba-fd13-4c22-b1a0-30e3199f4f60
|
ready_for_export
|
{
"name": [
"+1",
"_skip_reply",
"_skip_ranking",
"_skip_labeling"
],
"count": [
4,
5,
3,
1
]
}
|
{
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0.6666666666666666,
0.3333333333333333,
0.8333333333333334,
0.9166666666666666,
0.16666666666666666
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
a8a33068-3c37-4c30-89db-84fd08352dad
|
e4fa33ba-fd13-4c22-b1a0-30e3199f4f60
|
2bd4d452-8238-4c38-bdb8-7c658eaa2fe8
|
2023-03-25T08:10:10.009286+00:00
|
In the shadow of shattered steel, the stranger stumbled, seeking solace,
Under an ashen sky, an eerie echo of events unfolded.
Battered, bruised by brutal fate, bewildered and bewildering,
Every attempt to entreat, to encounter - ignored, evaded.
Grim and gaunt, the ghostly ground gave no comfort or compass,
In this odd, otherworldly odyssey, where once was warmth, wistful whispers.
Cruel cacophony of confusion, he cried for connection, for caring,
Urgent undercurrents of unspoken understanding, unanswered.
Manifold memories marred by melancholy, he marched, musing,
Alternating between agony and an almost apathetic acceptance.
Destiny deemed him a drifting wraith, a wandering whisper, a witness,
Isolated in the interstices of existence, the intersection of invisible.
Through twisted trees and tortured terrain, he traversed tirelessly,
Over open, opaque oceans of uncertainty, unfathomable and unforgiving.
Fearful phantoms flickered and fluttered in the fickle, fleeting light,
Ebbing, ever evasive, ethereal emotions engulfed him, escaping explanation.
A sudden shiver, the stark, staggering truth struck him like slivers of ice,
Impaled upon the infinite, the insurmountable: he was immaterial, impalpable.
No more man, but a memory, a mirage, a mote in the merciless maelstrom,
Unraveled, unanchored, untethered in the vast void of vanishing vibrations.
In the cold crepuscular chiaroscuro, the curtain closed on his corporeal chapter,
And he, an apparition adrift, surrendered to the silent, somber sanctuary of shadows.
|
assistant
|
en
| 3 | true | false | 0 | false | null |
{
"toxicity": 0.0035220289137214422,
"severe_toxicity": 0.000058334640925750136,
"obscene": 0.0003560019249562174,
"identity_attack": 0.0001805092761060223,
"insult": 0.002301166532561183,
"threat": 0.00008404579421039671,
"sexual_explicit": 0.00011015120981028304
}
|
e4fa33ba-fd13-4c22-b1a0-30e3199f4f60
|
ready_for_export
|
{
"name": [
"+1",
"_skip_reply",
"_skip_labeling"
],
"count": [
2,
1,
5
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0,
0.75,
0,
0.3333333333333333,
0.75,
0.75,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
024b1db0-cd46-4439-a091-ab444e63f7d3
|
a8a33068-3c37-4c30-89db-84fd08352dad
|
2d40e94c-40ed-4e00-a66e-454c0401c8ad
|
2023-03-27T12:28:06.184887+00:00
|
What literary or cinematic works come to mind when reading this poem, and how do they relate to the themes of loss, isolation, and the supernatural that are present in the poem?
|
prompter
|
en
| 3 | true | false | null | false | null |
{
"toxicity": 0.00034738407703116536,
"severe_toxicity": 0.000025394932890776545,
"obscene": 0.00016147695714607835,
"identity_attack": 0.00008809669088805094,
"insult": 0.00019264823640696704,
"threat": 0.000029295106287463568,
"sexual_explicit": 0.000023904718545963988
}
|
e4fa33ba-fd13-4c22-b1a0-30e3199f4f60
|
ready_for_export
| null |
{
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0.9166666666666666,
0.16666666666666666,
0.16666666666666666,
0.8333333333333334,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
cbc92b75-b76c-428e-82d2-8bfbd0439646
|
e4fa33ba-fd13-4c22-b1a0-30e3199f4f60
|
945cfc89-4366-4c3c-a779-a619fcf6454f
|
2023-03-25T12:40:06.664331+00:00
|
Silent, staggering, still in shock
Seeking someone to soothe his soul
Invisible, ignored, no one will stop
Stopping, staring, standing alone
Pain pulsating, palpable and pure
Pouring from his pores, a powerful surge
A phantom, a figment, a forgotten allure
Appearing aimlessly, adrift and submerged
Unseen by all, unacknowledged, unheard
Unsure of what happened, he wanders along
Vowels, consonants, all blending absurd
As he realizes, he's not alive, but gone
Gone from this world, gone from this place
Vanished from life, with no trace
Invisible, insubstantial, a ghostly embrace
Embracing the end, with all his grace
|
assistant
|
en
| 3 | true | false | 1 | false | null |
{
"toxicity": 0.11956225335597992,
"severe_toxicity": 0.00004614485806087032,
"obscene": 0.0005014617345295846,
"identity_attack": 0.00021602520428132266,
"insult": 0.11259856820106506,
"threat": 0.00010869128891499713,
"sexual_explicit": 0.00009330586181022227
}
|
e4fa33ba-fd13-4c22-b1a0-30e3199f4f60
|
ready_for_export
|
{
"name": [
"+1",
"-1"
],
"count": [
2,
1
]
}
|
{
"name": [
"spam",
"fails_task",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"helpfulness",
"creativity",
"violence"
],
"value": [
0,
0.3333333333333333,
0,
0,
0,
0,
0,
0.8333333333333334,
0,
0.16666666666666666,
0.75,
1,
0
],
"count": [
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3,
3
]
}
|
604df0ac-5c5b-487a-9249-bcb0d143f315
|
cbc92b75-b76c-428e-82d2-8bfbd0439646
|
70f38e30-c607-4652-9c8d-2366839ac519
|
2023-03-25T23:46:04.913468+00:00
|
Can you translate this poem into Spanish while preserving the rhyming pattern? Could you also recommend similar poems that I will be able to read?
|
prompter
|
en
| 3 | true | false | null | false | null |
{
"toxicity": 0.0003588096296880394,
"severe_toxicity": 0.00003118034510407597,
"obscene": 0.00014490091416519135,
"identity_attack": 0.0001440279884263873,
"insult": 0.00017546696471981704,
"threat": 0.00004146434002905153,
"sexual_explicit": 0.000024551274691475555
}
|
e4fa33ba-fd13-4c22-b1a0-30e3199f4f60
|
ready_for_export
|
{
"name": [
"+1",
"_skip_reply",
"_skip_ranking"
],
"count": [
3,
2,
9
]
}
|
{
"name": [
"spam",
"lang_mismatch",
"pii",
"not_appropriate",
"hate_speech",
"sexual_content",
"quality",
"toxicity",
"humor",
"creativity",
"violence"
],
"value": [
0,
0,
0,
0,
0,
0,
0.9166666666666666,
0.125,
0.125,
0.875,
0
],
"count": [
3,
3,
2,
2,
2,
2,
3,
2,
2,
2,
2
]
}
|
Subsets and Splits
SQL Console for OpenAssistant/oasst2
Reveals the structure of conversations by pairing prompts with their corresponding responses, highlighting the ranking of assistant responses for English-language messages.
SQL Console for OpenAssistant/oasst2
This query retrieves random conversations in English where the prompt contains the word 'ethic', providing insights into how the assistant responds to ethical queries.
Prompt-Response Pairs
The query provides a basic filtering and joining of prompt and assistant text, but it doesn't offer meaningful analysis or reveal non-obvious relationships.
Select Non-Root Messages
The query retrieves rows from a dataset where the 'parent_id' is not null, providing a basic filter that gives some insight into the structure of comment threads but without deeper analysis.
Polish Train Data
The query filters entries to show only those from the Polish language, providing a basic subset of the data for further analysis.
Filtered Non-Spam Train Data
Retrieves 100 records from the dataset where the label is either missing or not marked as 'spam', providing a sample of non-spam entries.