Datasets:
Tasks:
Text Classification
Modalities:
Text
Formats:
parquet
Sub-tasks:
multi-class-classification
Languages:
English
Size:
100K - 1M
License:
Commit
·
740c950
0
Parent(s):
Update files from the datasets library (from 1.0.0)
Browse filesRelease notes: https://github.com/huggingface/datasets/releases/tag/1.0.0
- .gitattributes +27 -0
- coarse_discourse.py +117 -0
- dataset_infos.json +1 -0
- dummy/0.1.0/dummy_data.zip +3 -0
.gitattributes
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*.7z filter=lfs diff=lfs merge=lfs -text
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*.bin filter=lfs diff=lfs merge=lfs -text
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*.bin.* filter=lfs diff=lfs merge=lfs -text
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*.bz2 filter=lfs diff=lfs merge=lfs -text
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*.ftz filter=lfs diff=lfs merge=lfs -text
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*.h5 filter=lfs diff=lfs merge=lfs -text
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*.joblib filter=lfs diff=lfs merge=lfs -text
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*.lfs.* filter=lfs diff=lfs merge=lfs -text
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*.model filter=lfs diff=lfs merge=lfs -text
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*.msgpack filter=lfs diff=lfs merge=lfs -text
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*.onnx filter=lfs diff=lfs merge=lfs -text
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*.ot filter=lfs diff=lfs merge=lfs -text
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*.parquet filter=lfs diff=lfs merge=lfs -text
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*.pb filter=lfs diff=lfs merge=lfs -text
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*.pt filter=lfs diff=lfs merge=lfs -text
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*.pth filter=lfs diff=lfs merge=lfs -text
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*.rar filter=lfs diff=lfs merge=lfs -text
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saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.tar.* filter=lfs diff=lfs merge=lfs -text
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*.tflite filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zstandard filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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coarse_discourse.py
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"""TODO(coarse_discourse): Add a description here."""
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from __future__ import absolute_import, division, print_function
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import json
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import os
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import datasets
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# TODO(coarse_discourse): BibTeX citation
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_CITATION = """\
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@inproceedings{coarsediscourse, title={Characterizing Online Discussion Using Coarse Discourse Sequences}, author={Zhang, Amy X. and Culbertson, Bryan and Paritosh, Praveen}, booktitle={Proceedings of the 11th International AAAI Conference on Weblogs and Social Media}, series={ICWSM '17}, year={2017}, location = {Montreal, Canada} }
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"""
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# TODO(coarse_discourse):
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_DESCRIPTION = """\
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dataset contains discourse annotation and relation on threads from reddit during 2016
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"""
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_URL = "https://github.com/google-research-datasets/coarse-discourse/archive/master.zip"
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class CoarseDiscourse(datasets.GeneratorBasedBuilder):
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"""TODO(coarse_discourse): Short description of my dataset."""
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# TODO(coarse_discourse): Set up version.
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VERSION = datasets.Version("0.1.0")
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def _info(self):
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# TODO(coarse_discourse): Specifies the datasets.DatasetInfo object
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return datasets.DatasetInfo(
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# This is the description that will appear on the datasets page.
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description=_DESCRIPTION,
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# datasets.features.FeatureConnectors
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features=datasets.Features(
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{
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# These are the features of your dataset like images, labels ...
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"title": datasets.Value("string"),
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"is_self_post": datasets.Value("bool"),
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"subreddit": datasets.Value("string"),
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"url": datasets.Value("string"),
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"majority_link": datasets.Value("string"),
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"is_first_post": datasets.Value("bool"),
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"majority_type": datasets.Value("string"),
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"id_post": datasets.Value("string"),
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"post_depth": datasets.Value("int32"),
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"in_reply_to": datasets.Value("string"),
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"annotations": datasets.features.Sequence(
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{
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"annotator": datasets.Value("string"),
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"link_to_post": datasets.Value("string"),
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"main_type": datasets.Value("string"),
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}
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),
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}
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),
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# If there's a common (input, target) tuple from the features,
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# specify them here. They'll be used if as_supervised=True in
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# builder.as_dataset.
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supervised_keys=None,
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# Homepage of the dataset for documentation
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homepage="https://github.com/google-research-datasets/coarse-discourse",
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager):
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"""Returns SplitGenerators."""
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# TODO(coarse_discourse): Downloads the data and defines the splits
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# dl_manager is a datasets.download.DownloadManager that can be used to
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# download and extract URLs
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dl_dir = dl_manager.download_and_extract(_URL)
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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# These kwargs will be passed to _generate_examples
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gen_kwargs={
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"filepath": os.path.join(dl_dir, "coarse-discourse-master", "coarse_discourse_dataset.json")
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},
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),
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]
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def _generate_examples(self, filepath):
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"""Yields examples."""
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# TODO(coarse_discourse): Yields (key, example) tuples from the dataset
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with open(filepath, encoding="utf-8") as f:
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for id_, row in enumerate(f):
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data = json.loads(row)
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url = data.get("url", "")
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is_self_post = data.get("is_self_post", "")
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subreddit = data.get("subreddit", "")
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title = data.get("title", "")
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posts = data.get("posts", "")
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for id1, post in enumerate(posts):
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maj_link = post.get("majority_link", "")
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maj_type = post.get("majority_type", "")
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id_post = post.get("id", "")
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is_first_post = post.get("is_firs_post", "")
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post_depth = post.get("post_depth", -1)
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in_reply_to = post.get("in_reply_to", "")
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annotations = post["annotations"]
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annotators = [annotation.get("annotator", "") for annotation in annotations]
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main_types = [annotation.get("main_type", "") for annotation in annotations]
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link_posts = [annotation.get("linkk_to_post", "") for annotation in annotations]
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yield str(id_) + "_" + str(id1), {
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"title": title,
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"is_self_post": is_self_post,
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"subreddit": subreddit,
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"url": url,
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"majority_link": maj_link,
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"is_first_post": is_first_post,
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"majority_type": maj_type,
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"id_post": id_post,
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"post_depth": post_depth,
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"in_reply_to": in_reply_to,
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"annotations": {"annotator": annotators, "link_to_post": link_posts, "main_type": main_types},
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}
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dataset_infos.json
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{"default": {"description": "dataset contains discourse annotation and relation on threads from reddit during 2016\n", "citation": "@inproceedings{coarsediscourse, title={Characterizing Online Discussion Using Coarse Discourse Sequences}, author={Zhang, Amy X. and Culbertson, Bryan and Paritosh, Praveen}, booktitle={Proceedings of the 11th International AAAI Conference on Weblogs and Social Media}, series={ICWSM '17}, year={2017}, location = {Montreal, Canada} }\n", "homepage": "https://github.com/google-research-datasets/coarse-discourse", "license": "", "features": {"title": {"dtype": "string", "id": null, "_type": "Value"}, "is_self_post": {"dtype": "bool", "id": null, "_type": "Value"}, "subreddit": {"dtype": "string", "id": null, "_type": "Value"}, "url": {"dtype": "string", "id": null, "_type": "Value"}, "majority_link": {"dtype": "string", "id": null, "_type": "Value"}, "is_first_post": {"dtype": "bool", "id": null, "_type": "Value"}, "majority_type": {"dtype": "string", "id": null, "_type": "Value"}, "id_post": {"dtype": "string", "id": null, "_type": "Value"}, "post_depth": {"dtype": "int32", "id": null, "_type": "Value"}, "in_reply_to": {"dtype": "string", "id": null, "_type": "Value"}, "annotations": {"feature": {"annotator": {"dtype": "string", "id": null, "_type": "Value"}, "link_to_post": {"dtype": "string", "id": null, "_type": "Value"}, "main_type": {"dtype": "string", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}}, "supervised_keys": null, "builder_name": "coarse_discourse", "config_name": "default", "version": {"version_str": "0.1.0", "description": null, "datasets_version_to_prepare": null, "major": 0, "minor": 1, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 45443464, "num_examples": 116357, "dataset_name": "coarse_discourse"}}, "download_checksums": {"https://github.com/google-research-datasets/coarse-discourse/archive/master.zip": {"num_bytes": 4636201, "checksum": "8e1e685c5907a6d654be8b8ed307522fd91ca919f503713fd1627fbe3d43c3cd"}}, "download_size": 4636201, "dataset_size": 45443464, "size_in_bytes": 50079665}}
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dummy/0.1.0/dummy_data.zip
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version https://git-lfs.github.com/spec/v1
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oid sha256:0e3c0fcee52339651069d3a9189511cb4723eb7643836e64c9f0bf8fcc49b4db
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size 1128
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