Datasets:
Convert dataset to Parquet
#4
by
KennethEnevoldsen
- opened
- DanFever/train-00000-of-00001.parquet +3 -0
- README.md +38 -0
- danfever.py +0 -119
- dataset_infos.json +0 -1
DanFever/train-00000-of-00001.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:838969d8df3bd993d47a374d84f507c7f2bbc5b1b23e5f8615d59bf9dee62ea7
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size 721856
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README.md
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@@ -22,6 +22,44 @@ paperswithcode_id: danfever
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pretty_name: DanFEVER
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tags:
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- knowledge-verification
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---
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pretty_name: DanFEVER
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tags:
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- knowledge-verification
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dataset_info:
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config_name: DanFever
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features:
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- name: id
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dtype: string
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- name: claim
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dtype: string
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- name: label
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dtype:
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class_label:
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names:
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'0': Refuted
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'1': Supported
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'2': NotEnoughInfo
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- name: evidence_extract
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dtype: string
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- name: verifiable
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dtype:
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class_label:
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names:
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'0': NotVerifiable
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'1': Verifiable
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- name: evidence
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dtype: string
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- name: original_id
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dtype: string
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splits:
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- name: train
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num_bytes: 2940646
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num_examples: 6407
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download_size: 721856
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dataset_size: 2940646
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configs:
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- config_name: DanFever
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data_files:
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- split: train
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path: DanFever/train-*
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default: true
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---
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danfever.py
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# coding=utf-8
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# Copyright 2020 HuggingFace Datasets Authors.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# Lint as: python3
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"""DanFEVER: A FEVER dataset for Danish"""
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import csv
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import os
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import datasets
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logger = datasets.logging.get_logger(__name__)
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_CITATION = """\
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@inproceedings{norregaard-derczynski-2021-danfever,
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title = "{D}an{FEVER}: claim verification dataset for {D}anish",
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author = "N{\o}rregaard, Jeppe and
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Derczynski, Leon",
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booktitle = "Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa)",
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month = may # " 31--2 " # jun,
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year = "2021",
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address = "Reykjavik, Iceland (Online)",
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publisher = {Link{\"o}ping University Electronic Press, Sweden},
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url = "https://aclanthology.org/2021.nodalida-main.47",
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pages = "422--428",
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abstract = "We present a dataset, DanFEVER, intended for multilingual misinformation research. The dataset is in Danish and has the same format as the well-known English FEVER dataset. It can be used for testing methods in multilingual settings, as well as for creating models in production for the Danish language.",
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}
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"""
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_DESCRIPTION = """\
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"""
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_URL = "https://media.githubusercontent.com/media/StrombergNLP/danfever/main/tsv/da_fever.tsv"
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class DanFeverConfig(datasets.BuilderConfig):
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"""BuilderConfig for DanFever"""
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def __init__(self, **kwargs):
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"""BuilderConfig DanFever.
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Args:
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**kwargs: keyword arguments forwarded to super.
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"""
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super(DanFeverConfig, self).__init__(**kwargs)
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class DanFever(datasets.GeneratorBasedBuilder):
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"""DanFever dataset."""
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BUILDER_CONFIGS = [
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DanFeverConfig(name="DanFever", version=datasets.Version("1.0.0"), description="FEVER dataset for Danish"),
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]
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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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"id": datasets.Value("string"),
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"claim": datasets.Value("string"),
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"label": datasets.features.ClassLabel(
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names=[
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"Refuted",
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"Supported",
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"NotEnoughInfo",
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]
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),
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"evidence_extract": datasets.Value("string"),
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"verifiable": datasets.features.ClassLabel(
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names=[
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"NotVerifiable",
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"Verifiable",
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]
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),
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"evidence": datasets.Value("string"),
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"original_id": datasets.Value("string"),
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}
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),
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supervised_keys=None,
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homepage="https://stromberg.ai/publication/danfever/",
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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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downloaded_file = dl_manager.download_and_extract(_URL)
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return [
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_file}),
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]
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def _generate_examples(self, filepath):
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logger.info("⏳ Generating examples from = %s", filepath)
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with open(filepath, encoding="utf-8") as f:
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data_reader = csv.DictReader(f, delimiter="\t", quotechar='"')
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guid = 0
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for instance in data_reader:
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instance.pop('nr.')
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instance["original_id"] = instance.pop('id')
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instance["id"] = str(guid)
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yield guid, instance
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guid += 1
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dataset_infos.json
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{"DanFever": {"description": "\n", "citation": "@inproceedings{norregaard-derczynski-2021-danfever,\n title = \"{D}an{FEVER}: claim verification dataset for {D}anish\",\n author = \"N{\\o}rregaard, Jeppe and\n Derczynski, Leon\",\n booktitle = \"Proceedings of the 23rd Nordic Conference on Computational Linguistics (NoDaLiDa)\",\n month = may # \" 31--2 \" # jun,\n year = \"2021\",\n address = \"Reykjavik, Iceland (Online)\",\n publisher = {Link{\"o}ping University Electronic Press, Sweden},\n url = \"https://aclanthology.org/2021.nodalida-main.47\",\n pages = \"422--428\",\n abstract = \"We present a dataset, DanFEVER, intended for multilingual misinformation research. The dataset is in Danish and has the same format as the well-known English FEVER dataset. It can be used for testing methods in multilingual settings, as well as for creating models in production for the Danish language.\",\n}\n", "homepage": "https://stromberg.ai/publication/danfever/", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "claim": {"dtype": "string", "id": null, "_type": "Value"}, "label": {"num_classes": 3, "names": ["Refuted", "Supported", "NotEnoughInfo"], "id": null, "_type": "ClassLabel"}, "evidence_extract": {"dtype": "string", "id": null, "_type": "Value"}, "verifiable": {"num_classes": 2, "names": ["NotVerifiable", "Verifiable"], "id": null, "_type": "ClassLabel"}, "evidence": {"dtype": "string", "id": null, "_type": "Value"}, "original_id": {"dtype": "string", "id": null, "_type": "Value"}}, "post_processed": null, "supervised_keys": null, "task_templates": null, "builder_name": "dan_fever", "config_name": "DanFever", "version": {"version_str": "1.0.0", "description": null, "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 2940646, "num_examples": 6407, "dataset_name": "dan_fever"}}, "download_checksums": {"https://media.githubusercontent.com/media/StrombergNLP/danfever/main/tsv/da_fever.tsv": {"num_bytes": 2952080, "checksum": "4ca3e4ee85ff8e017c49cf05235c54a00655db54c5c0a728cb4015e71b4e3efa"}}, "download_size": 2952080, "post_processing_size": null, "dataset_size": 2940646, "size_in_bytes": 5892726}}
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