Datasets:

Languages:
English
Multilinguality:
monolingual
Size Categories:
10K<n<100K
Language Creators:
found
Annotations Creators:
crowdsourced
Source Datasets:
original
Tags:
License:
albertvillanova HF staff commited on
Commit
27cb3a4
1 Parent(s): 2abf38b

Delete loading script

Browse files
Files changed (1) hide show
  1. wiki_qa.py +0 -96
wiki_qa.py DELETED
@@ -1,96 +0,0 @@
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- """TODO(wiki_qa): Add a description here."""
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-
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-
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- import csv
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- import os
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-
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- import datasets
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-
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-
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- # TODO(wiki_qa): BibTeX citation
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- _CITATION = """\
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- @InProceedings{YangYihMeek:EMNLP2015:WikiQA,
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- author = {{Yi}, Yang and {Wen-tau}, Yih and {Christopher} Meek},
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- title = "{WikiQA: A Challenge Dataset for Open-Domain Question Answering}",
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- journal = {Association for Computational Linguistics},
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- year = 2015,
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- doi = {10.18653/v1/D15-1237},
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- pages = {2013–2018},
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- }
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- """
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-
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- # TODO(wiki_qa):
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- _DESCRIPTION = """\
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- Wiki Question Answering corpus from Microsoft
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- """
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-
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- _DATA_URL = "https://download.microsoft.com/download/E/5/f/E5FCFCEE-7005-4814-853D-DAA7C66507E0/WikiQACorpus.zip" # 'https://www.microsoft.com/en-us/download/confirmation.aspx?id=52419'
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-
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-
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- class WikiQa(datasets.GeneratorBasedBuilder):
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- """TODO(wiki_qa): Short description of my dataset."""
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-
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- # TODO(wiki_qa): Set up version.
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- VERSION = datasets.Version("0.1.0")
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-
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- def _info(self):
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- # TODO(wiki_qa): 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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- "question_id": datasets.Value("string"),
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- "question": datasets.Value("string"),
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- "document_title": datasets.Value("string"),
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- "answer": datasets.Value("string"),
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- "label": datasets.features.ClassLabel(num_classes=2),
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- # These are the features of your dataset like images, labels ...
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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://www.microsoft.com/en-us/download/details.aspx?id=52419",
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- citation=_CITATION,
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- )
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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(wiki_qa): 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(_DATA_URL)
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- dl_dir = os.path.join(dl_dir, "WikiQACorpus")
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- # dl_dir = os.path.join(dl_dir, '')
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- return [
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- datasets.SplitGenerator(
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- name=datasets.Split.TEST, gen_kwargs={"filepath": os.path.join(dl_dir, "WikiQA-test.tsv")}
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- ),
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- datasets.SplitGenerator(
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- name=datasets.Split.VALIDATION, gen_kwargs={"filepath": os.path.join(dl_dir, "WikiQA-dev.tsv")}
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- ),
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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={"filepath": os.path.join(dl_dir, "WikiQA-train.tsv")},
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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(wiki_qa): Yields (key, example) tuples from the dataset
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-
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- with open(filepath, encoding="utf-8") as f:
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- reader = csv.DictReader(f, delimiter="\t", quoting=csv.QUOTE_NONE)
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- for idx, row in enumerate(reader):
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- yield idx, {
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- "question_id": row["QuestionID"],
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- "question": row["Question"],
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- "document_title": row["DocumentTitle"],
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- "answer": row["Sentence"],
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- "label": row["Label"],
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- }