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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
- dataset_infos.json +1 -0
- dummy/0.1.0/dummy_data.zip +3 -0
- qa_zre.py +100 -0
.gitattributes
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*.7z filter=lfs diff=lfs merge=lfs -text
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*.arrow 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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*.gz 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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*.tgz filter=lfs diff=lfs merge=lfs -text
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*.xz 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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dataset_infos.json
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{"default": {"description": "A dataset reducing relation extraction to simple reading comprehension questions\n", "citation": "@inproceedings{levy-etal-2017-zero,\n title = \"Zero-Shot Relation Extraction via Reading Comprehension\",\n author = \"Levy, Omer and\n Seo, Minjoon and\n Choi, Eunsol and\n Zettlemoyer, Luke\",\n booktitle = \"Proceedings of the 21st Conference on Computational Natural Language Learning ({C}o{NLL} 2017)\",\n month = aug,\n year = \"2017\",\n address = \"Vancouver, Canada\",\n publisher = \"Association for Computational Linguistics\",\n url = \"https://www.aclweb.org/anthology/K17-1034\",\n doi = \"10.18653/v1/K17-1034\",\n pages = \"333--342\",\n}\n", "homepage": "http://nlp.cs.washington.edu/zeroshot", "license": "", "features": {"relation": {"dtype": "string", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "subject": {"dtype": "string", "id": null, "_type": "Value"}, "context": {"dtype": "string", "id": null, "_type": "Value"}, "answers": {"feature": {"dtype": "string", "id": null, "_type": "Value"}, "length": -1, "id": null, "_type": "Sequence"}}, "supervised_keys": null, "builder_name": "qa_zre", "config_name": "default", "version": {"version_str": "0.1.0", "description": null, "datasets_version_to_prepare": null, "major": 0, "minor": 1, "patch": 0}, "splits": {"test": {"name": "test", "num_bytes": 29410194, "num_examples": 120000, "dataset_name": "qa_zre"}, "validation": {"name": "validation", "num_bytes": 1481430, "num_examples": 6000, "dataset_name": "qa_zre"}, "train": {"name": "train", "num_bytes": 2054954011, "num_examples": 8400000, "dataset_name": "qa_zre"}}, "download_checksums": {"http://nlp.cs.washington.edu/zeroshot/relation_splits.tar.bz2": {"num_bytes": 516061636, "checksum": "e33d0e367b6e837370da17a2d09d217e0a92f8d180f7abb3fd543a2d1726b2b4"}}, "download_size": 516061636, "dataset_size": 2085845635, "size_in_bytes": 2601907271}}
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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 sha256:4bcada04416b17bd18bb40d960aa6133a93e5e03de793b8c218672e7eb607e81
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size 10404
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qa_zre.py
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"""A dataset reducing relation extraction to simple reading comprehension questions"""
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from __future__ import absolute_import, division, print_function
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import csv
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import os
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import datasets
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_CITATION = """\
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@inproceedings{levy-etal-2017-zero,
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title = "Zero-Shot Relation Extraction via Reading Comprehension",
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author = "Levy, Omer and
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Seo, Minjoon and
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Choi, Eunsol and
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Zettlemoyer, Luke",
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booktitle = "Proceedings of the 21st Conference on Computational Natural Language Learning ({C}o{NLL} 2017)",
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month = aug,
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year = "2017",
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address = "Vancouver, Canada",
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publisher = "Association for Computational Linguistics",
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url = "https://www.aclweb.org/anthology/K17-1034",
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doi = "10.18653/v1/K17-1034",
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pages = "333--342",
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}
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"""
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_DESCRIPTION = """\
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A dataset reducing relation extraction to simple reading comprehension questions
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"""
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_DATA_URL = "http://nlp.cs.washington.edu/zeroshot/relation_splits.tar.bz2"
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class QaZre(datasets.GeneratorBasedBuilder):
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"""QA-ZRE: Reducing relation extraction to simple reading comprehension questions"""
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VERSION = datasets.Version("0.1.0")
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def _info(self):
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=datasets.Features(
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{
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"relation": datasets.Value("string"),
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"question": datasets.Value("string"),
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"subject": datasets.Value("string"),
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"context": datasets.Value("string"),
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"answers": datasets.features.Sequence(datasets.Value("string")),
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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="http://nlp.cs.washington.edu/zeroshot",
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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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dl_dir = dl_manager.download_and_extract(_DATA_URL)
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dl_dir = os.path.join(dl_dir, "relation_splits")
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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gen_kwargs={
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"filepaths": [os.path.join(dl_dir, "test." + str(i)) for i in range(10)],
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},
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),
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datasets.SplitGenerator(
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name=datasets.Split.VALIDATION,
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gen_kwargs={
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"filepaths": [os.path.join(dl_dir, "dev." + str(i)) for i in range(10)],
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},
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),
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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gen_kwargs={
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"filepaths": [os.path.join(dl_dir, "train." + str(i)) for i in range(10)],
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},
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),
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]
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def _generate_examples(self, filepaths):
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"""Yields examples."""
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for filepath in filepaths:
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with open(filepath, encoding="utf-8") as f:
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data = csv.reader(f, delimiter="\t")
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for idx, row in enumerate(data):
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yield idx, {
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"relation": row[0],
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"question": row[1],
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"subject": row[2],
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"context": row[3],
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"answers": row[4:],
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}
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