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README.md

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----
-annotations_creators:
-- found
-language_creators:
-- found
-language:
-- en
-license:
-- unknown
-multilinguality:
-- monolingual
-pretty_name: ontonotes_english
-size_categories:
-- 10K<n<100K
-source_datasets:
-- extended|other
-task_categories:
-- token-classification
-task_ids:
-- named-entity-recognition
----
-
-# Dataset Card for ontonotes_english
-
-## Table of Contents
-- [Table of Contents](#table-of-contents)
-- [Dataset Description](#dataset-description)
-  - [Dataset Summary](#dataset-summary)
-  - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
-  - [Languages](#languages)
-- [Dataset Structure](#dataset-structure)
-  - [Data Instances](#data-instances)
-  - [Data Fields](#data-fields)
-  - [Data Splits](#data-splits)
-- [Dataset Creation](#dataset-creation)
-  - [Curation Rationale](#curation-rationale)
-  - [Source Data](#source-data)
-  - [Annotations](#annotations)
-  - [Personal and Sensitive Information](#personal-and-sensitive-information)
-- [Considerations for Using the Data](#considerations-for-using-the-data)
-  - [Social Impact of Dataset](#social-impact-of-dataset)
-  - [Discussion of Biases](#discussion-of-biases)
-  - [Other Known Limitations](#other-known-limitations)
-- [Additional Information](#additional-information)
-  - [Dataset Curators](#dataset-curators)
-  - [Licensing Information](#licensing-information)
-  - [Citation Information](#citation-information)
-  - [Contributions](#contributions)
-
-## Dataset Description
-
-- **Homepage:** [CoNLL-2012 Shared Task](https://conll.cemantix.org/2012/data.html), [Author's page](https://cemantix.org/data/ontonotes.html)
-- **Repository:**
-- **Paper:** [Towards Robust Linguistic Analysis using OntoNotes](https://aclanthology.org/W13-3516/)
-- **Leaderboard:** [Papers With Code](https://paperswithcode.com/sota/named-entity-recognition-ner-on-ontonotes-v5)
-- **Point of Contact:**
-
-### Dataset Summary
-
-This is preprocessed version of what I assume is OntoNotes v5.0.
-
-Instead of having sentences stored in files, files are unpacked and sentences are the rows now. Also, fields were renamed in order to match [conll2003](https://huggingface.co/datasets/conll2003).
-
-The source of data is from private repository, which in turn got data from another public repository, location of which is unknown :)
-
-Since data from all repositories had no license (creator of the private repository told me so), there should be no licensing issues. But bear in mind, I don't give any guarantees that this is real OntoNotes, and may differ as a result.
-
-### Supported Tasks and Leaderboards
-
-- [Named Entity Recognition on Ontonotes v5 (English)](https://paperswithcode.com/sota/named-entity-recognition-ner-on-ontonotes-v5)
-- [Coreference Resolution on OntoNotes](https://paperswithcode.com/sota/coreference-resolution-on-ontonotes)
-- [Semantic Role Labeling on OntoNotes](https://paperswithcode.com/sota/semantic-role-labeling-on-ontonotes)
-
-### Languages
-
-English
-
-## Dataset Structure
-
-### Data Instances
-
-```
-{
-    'tokens': ['Well', ',', 'the', 'Hundred', 'Regiments', 'Offensive', 'was', 'divided', 'into', 'three', 'phases', '.'],
-    'ner_tags': [0, 0, 29, 30, 30, 30, 0, 0, 0, 27, 0, 0]
-}
-```
-
-### Data Fields
-
-- **`tokens`** (*`List[str]`*) : **`words`** in original dataset
-- **`ner_tags`** (*`List[ClassLabel]`*) : **`named_entities`** in original dataset. The BIO tags for named entities in the sentence. 
-  - tag set : `datasets.ClassLabel(num_classes=37, names=["O", "B-PERSON", "I-PERSON", "B-NORP", "I-NORP", "B-FAC", "I-FAC", "B-ORG", "I-ORG", "B-GPE", "I-GPE", "B-LOC", "I-LOC", "B-PRODUCT", "I-PRODUCT", "B-DATE", "I-DATE", "B-TIME", "I-TIME", "B-PERCENT", "I-PERCENT", "B-MONEY", "I-MONEY", "B-QUANTITY", "I-QUANTITY", "B-ORDINAL", "I-ORDINAL", "B-CARDINAL", "I-CARDINAL", "B-EVENT", "I-EVENT", "B-WORK_OF_ART", "I-WORK_OF_ART", "B-LAW", "I-LAW", "B-LANGUAGE", "I-LANGUAGE",])`
-
-### Data Splits
-
-_train_, _validation_, and _test_
-
-## Dataset Creation
-
-### Curation Rationale
-
-[More Information Needed]
-
-### Source Data
-
-#### Initial Data Collection and Normalization
-
-[More Information Needed]
-
-#### Who are the source language producers?
-
-[More Information Needed]
-
-### Annotations
-
-#### Annotation process
-
-[More Information Needed]
-
-#### Who are the annotators?
-
-[More Information Needed]
-
-### Personal and Sensitive Information
-
-[More Information Needed]
-
-## Considerations for Using the Data
-
-### Social Impact of Dataset
-
-[More Information Needed]
-
-### Discussion of Biases
-
-[More Information Needed]
-
-### Other Known Limitations
-
-[More Information Needed]
-
-## Additional Information
-
-### Dataset Curators
-
-[More Information Needed]
-
-### Licensing Information
-
-No license
-
-### Citation Information
-
-```
-@inproceedings{pradhan-etal-2013-towards,
-    title = "Towards Robust Linguistic Analysis using {O}nto{N}otes",
-    author = {Pradhan, Sameer  and
-      Moschitti, Alessandro  and
-      Xue, Nianwen  and
-      Ng, Hwee Tou  and
-      Bj{\"o}rkelund, Anders  and
-      Uryupina, Olga  and
-      Zhang, Yuchen  and
-      Zhong, Zhi},
-    booktitle = "Proceedings of the Seventeenth Conference on Computational Natural Language Learning",
-    month = aug,
-    year = "2013",
-    address = "Sofia, Bulgaria",
-    publisher = "Association for Computational Linguistics",
-    url = "https://aclanthology.org/W13-3516",
-    pages = "143--152",
-}
-```
-
-### Contributions
-
-Thanks to the author of private repository, that uploaded this dataset.

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dataset_infos.json

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-{"SpeedOfMagic--ontonotes_english": {"description": "The shared task of CoNLL-2003 concerns language-independent named entity recognition. We will concentrate on\nfour types of named entities: persons, locations, organizations and names of miscellaneous entities that do\nnot belong to the previous three groups.\n\nThe CoNLL-2003 shared task data files contain four columns separated by a single space. Each word has been put on\na separate line and there is an empty line after each sentence. The first item on each line is a word, the second\na part-of-speech (POS) tag, the third a syntactic chunk tag and the fourth the named entity tag. The chunk tags\nand the named entity tags have the format I-TYPE which means that the word is inside a phrase of type TYPE. Only\nif two phrases of the same type immediately follow each other, the first word of the second phrase will have tag\nB-TYPE to show that it starts a new phrase. A word with tag O is not part of a phrase. Note the dataset uses IOB2\ntagging scheme, whereas the original dataset uses IOB1.\n\nFor more details see https://www.clips.uantwerpen.be/conll2003/ner/ and https://www.aclweb.org/anthology/W03-0419\n", "citation": "@inproceedings{tjong-kim-sang-de-meulder-2003-introduction,\n    title = \"Introduction to the {C}o{NLL}-2003 Shared Task: Language-Independent Named Entity Recognition\",\n    author = \"Tjong Kim Sang, Erik F.  and\n      De Meulder, Fien\",\n    booktitle = \"Proceedings of the Seventh Conference on Natural Language Learning at {HLT}-{NAACL} 2003\",\n    year = \"2003\",\n    url = \"https://www.aclweb.org/anthology/W03-0419\",\n    pages = \"142--147\",\n}\n", "homepage": "https://www.aclweb.org/anthology/W03-0419/", "license": "", "features": {"tokens": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}, "ner_tags": {"feature": {"num_classes": 37, "names": ["O", "B-PERSON", "I-PERSON", "B-NORP", "I-NORP", "B-FAC", "I-FAC", "B-ORG", "I-ORG", "B-GPE", "I-GPE", "B-LOC", "I-LOC", "B-PRODUCT", "I-PRODUCT", "B-DATE", "I-DATE", "B-TIME", "I-TIME", "B-PERCENT", "I-PERCENT", "B-MONEY", "I-MONEY", "B-QUANTITY", "I-QUANTITY", "B-ORDINAL", "I-ORDINAL", "B-CARDINAL", "I-CARDINAL", "B-EVENT", "I-EVENT", "B-WORK_OF_ART", "I-WORK_OF_ART", "B-LAW", "I-LAW", "B-LANGUAGE", "I-LANGUAGE"], "id": null, "_type": "ClassLabel"}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "conll2003", "config_name": "conll2003", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 18175257, "num_examples": 59924, "dataset_name": "ontonotes_english"}, "validation": {"name": "validation", "num_bytes": 4656610, "num_examples": 13900, "dataset_name": "ontonotes_english"}, "test": {"name": "test", "num_bytes": 2543937, "num_examples": 8262, "dataset_name": "ontonotes_english"}}, "download_checksums": null, "download_size": 4387753, "post_processing_size": null, "dataset_size": 25375804, "size_in_bytes": 29763557}}