Convert dataset to Parquet

#3
by albertvillanova HF staff - opened
README.md CHANGED
@@ -5,8 +5,6 @@ language_creators:
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  - crowdsourced
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  language:
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  - fr
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- language_bcp47:
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- - fr-FR
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  license:
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  - mit
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  multilinguality:
@@ -20,9 +18,11 @@ task_categories:
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  task_ids:
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  - extractive-qa
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  - open-domain-qa
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- paperswithcode_id: null
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  pretty_name: Piaf
 
 
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  dataset_info:
 
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  features:
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  - name: id
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  dtype: string
@@ -38,13 +38,18 @@ dataset_info:
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  dtype: string
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  - name: answer_start
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  dtype: int32
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- config_name: plain_text
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  splits:
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  - name: train
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- num_bytes: 3332905
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  num_examples: 3835
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- download_size: 1370384
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- dataset_size: 3332905
 
 
 
 
 
 
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  ---
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  # Dataset Card for Piaf
 
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  - crowdsourced
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  language:
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  - fr
 
 
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  license:
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  - mit
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  multilinguality:
 
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  task_ids:
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  - extractive-qa
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  - open-domain-qa
 
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  pretty_name: Piaf
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+ language_bcp47:
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+ - fr-FR
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  dataset_info:
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+ config_name: plain_text
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  features:
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  - name: id
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  dtype: string
 
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  dtype: string
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  - name: answer_start
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  dtype: int32
 
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  splits:
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  - name: train
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+ num_bytes: 3332877
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  num_examples: 3835
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+ download_size: 650352
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+ dataset_size: 3332877
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+ configs:
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+ - config_name: plain_text
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+ data_files:
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+ - split: train
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+ path: plain_text/train-*
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+ default: true
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  ---
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  # Dataset Card for Piaf
dataset_infos.json DELETED
@@ -1 +0,0 @@
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- {"plain_text": {"description": "Piaf is a reading comprehension dataset. This version, published in February 2020, contains 3835 questions on French Wikipedia.\n", "citation": "@InProceedings{keraron-EtAl:2020:LREC,\n author = {Keraron, Rachel and Lancrenon, Guillaume and Bras, Mathilde and Allary, Fr\u00e9d\u00e9ric and Moyse, Gilles and Scialom, Thomas and Soriano-Morales, Edmundo-Pavel and Staiano, Jacopo},\n title = {Project PIAF: Building a Native French Question-Answering Dataset},\n booktitle = {Proceedings of The 12th Language Resources and Evaluation Conference},\n month = {May},\n year = {2020},\n address = {Marseille, France},\n publisher = {European Language Resources Association},\n pages = {5483--5492},\n abstract = {Motivated by the lack of data for non-English languages, in particular for the evaluation of downstream tasks such as Question Answering, we present a participatory effort to collect a native French Question Answering Dataset. Furthermore, we describe and publicly release the annotation tool developed for our collection effort, along with the data obtained and preliminary baselines.},\n url = {https://www.aclweb.org/anthology/2020.lrec-1.673}\n}\n", "homepage": "https://piaf.etalab.studio", "license": "", "features": {"id": {"dtype": "string", "id": null, "_type": "Value"}, "title": {"dtype": "string", "id": null, "_type": "Value"}, "context": {"dtype": "string", "id": null, "_type": "Value"}, "question": {"dtype": "string", "id": null, "_type": "Value"}, "answers": {"feature": {"text": {"dtype": "string", "id": null, "_type": "Value"}, "answer_start": {"dtype": "int32", "id": null, "_type": "Value"}}, "length": -1, "id": null, "_type": "Sequence"}}, "post_processed": null, "supervised_keys": null, "task_templates": [{"task": "question-answering-extractive", "question_column": "question", "context_column": "context", "answers_column": "answers"}], "builder_name": "piaf", "config_name": "plain_text", "version": {"version_str": "1.0.0", "description": "", "major": 1, "minor": 0, "patch": 0}, "splits": {"train": {"name": "train", "num_bytes": 3332905, "num_examples": 3835, "dataset_name": "piaf"}}, "download_checksums": {"https://github.com/etalab-ia/piaf-code/raw/master/piaf-v1.0.json": {"num_bytes": 1370384, "checksum": "008229ccefa0195d7e809d777d33149cab03433059c9477bdbadb4838a277cd2"}}, "download_size": 1370384, "post_processing_size": null, "dataset_size": 3332905, "size_in_bytes": 4703289}}
 
 
piaf.py DELETED
@@ -1,139 +0,0 @@
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- # coding=utf-8
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- # Copyright 2020 The TensorFlow Datasets Authors and the 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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-
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- # Lint as: python3
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- """PIAF Question Answering Dataset"""
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-
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-
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- import json
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-
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- import datasets
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- from datasets.tasks import QuestionAnsweringExtractive
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-
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-
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- logger = datasets.logging.get_logger(__name__)
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-
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-
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- _CITATION = """\
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- @InProceedings{keraron-EtAl:2020:LREC,
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- author = {Keraron, Rachel and Lancrenon, Guillaume and Bras, Mathilde and Allary, Frédéric and Moyse, Gilles and Scialom, Thomas and Soriano-Morales, Edmundo-Pavel and Staiano, Jacopo},
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- title = {Project PIAF: Building a Native French Question-Answering Dataset},
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- booktitle = {Proceedings of The 12th Language Resources and Evaluation Conference},
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- month = {May},
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- year = {2020},
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- address = {Marseille, France},
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- publisher = {European Language Resources Association},
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- pages = {5483--5492},
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- abstract = {Motivated by the lack of data for non-English languages, in particular for the evaluation of downstream tasks such as Question Answering, we present a participatory effort to collect a native French Question Answering Dataset. Furthermore, we describe and publicly release the annotation tool developed for our collection effort, along with the data obtained and preliminary baselines.},
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- url = {https://www.aclweb.org/anthology/2020.lrec-1.673}
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- }
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- """
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-
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- _DESCRIPTION = """\
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- Piaf is a reading comprehension \
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- dataset. This version, published in February 2020, contains 3835 questions on French Wikipedia.
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- """
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-
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- _URLS = {"train": "https://github.com/etalab-ia/piaf-code/raw/master/piaf-v1.0.json"}
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-
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-
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- class PiafConfig(datasets.BuilderConfig):
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- """BuilderConfig for PIAF."""
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-
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- def __init__(self, **kwargs):
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- """BuilderConfig for PIAF.
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-
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- Args:
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- **kwargs: keyword arguments forwarded to super.
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- """
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- super(PiafConfig, self).__init__(**kwargs)
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-
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-
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- class Piaf(datasets.GeneratorBasedBuilder):
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- """The Piaf Question Answering Dataset. Version 1.0."""
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-
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- BUILDER_CONFIGS = [
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- PiafConfig(
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- name="plain_text",
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- version=datasets.Version("1.0.0", ""),
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- description="Plain text",
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- ),
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- ]
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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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- "title": datasets.Value("string"),
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- "context": datasets.Value("string"),
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- "question": datasets.Value("string"),
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- "answers": datasets.features.Sequence(
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- {
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- "text": datasets.Value("string"),
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- "answer_start": datasets.Value("int32"),
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- }
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- ),
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- }
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- ),
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- # No default supervised_keys (as we have to pass both question
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- # and context as input).
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- supervised_keys=None,
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- homepage="https://piaf.etalab.studio",
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- citation=_CITATION,
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- task_templates=[
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- QuestionAnsweringExtractive(
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- question_column="question", context_column="context", answers_column="answers"
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- )
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- ],
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- )
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-
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- def _split_generators(self, dl_manager):
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- urls_to_download = _URLS
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- downloaded_files = dl_manager.download_and_extract(urls_to_download)
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-
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- return [
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- datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"]}),
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- ]
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-
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- def _generate_examples(self, filepath):
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- """This function returns the examples in the raw (text) form."""
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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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- dataset = json.load(f)
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- for article in dataset["data"]:
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- title = article.get("title", "").strip()
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- for paragraph in article["paragraphs"]:
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- context = paragraph["context"].strip()
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- for qa in paragraph["qas"]:
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- question = qa["question"].strip()
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- id_ = qa["id"]
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-
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- answer_starts = [answer["answer_start"] for answer in qa["answers"]]
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- answers = [answer["text"].strip() for answer in qa["answers"]]
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-
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- # Features currently used are "context", "question", and "answers".
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- # Others are extracted here for the ease of future expansions.
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- yield id_, {
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- "title": title,
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- "context": context,
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- "question": question,
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- "id": id_,
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- "answers": {
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- "answer_start": answer_starts,
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- "text": answers,
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- },
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- }
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
plain_text/train-00000-of-00001.parquet ADDED
@@ -0,0 +1,3 @@
 
 
 
 
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:868b00642fd947182dd406becee1f7981c4ab69c2dc78ee5f0e6e7a42d98ebad
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+ size 650352