Commit
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f940ffe
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0629b4d
Update parquet files
Browse files- default/logiqa-test.parquet +3 -0
- default/logiqa-train.parquet +3 -0
- default/logiqa-validation.parquet +3 -0
- logiqa.py +0 -106
default/logiqa-test.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:eadb6c068d00b3787b5d0ed007c6ee2f0532df3010f3702417a8749b73e83835
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size 288759
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default/logiqa-train.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:5f47d4e157f6ae60278e870e7bc392e5cafc18e2cd285b36b87fff5b158425f0
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size 3682115
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default/logiqa-validation.parquet
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version https://git-lfs.github.com/spec/v1
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oid sha256:76aa870029d0eca60998a5ba523b32ab560ebabcc65f0e4ed2cac9e1dea12e25
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size 290455
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logiqa.py
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"""LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning"""
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import re
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import datasets
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logger = datasets.logging.get_logger(__name__)
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_HOMEPAGE = "https://github.com/lgw863/LogiQA-dataset"
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_DESCRIPTION = """\
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LogiQA is constructed from the logical comprehension problems from \
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publically available questions of the National Civil Servants Examination \
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of China, which are designed to test the civil servant candidates’ critical \
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thinking and problem solving. This dataset includes the English versions only; \
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the Chinese versions are available via the homepage/original source."""
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_CITATION = """\
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@article{liu2020logiqa,
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title={Logiqa: A challenge dataset for machine reading comprehension with logical reasoning},
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author={Liu, Jian and Cui, Leyang and Liu, Hanmeng and Huang, Dandan and Wang, Yile and Zhang, Yue},
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journal={arXiv preprint arXiv:2007.08124},
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year={2020}
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}
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"""
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_URLS = {
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"en_train": "https://raw.githubusercontent.com/lgw863/LogiQA-dataset/master/Train.txt",
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"en_test": "https://raw.githubusercontent.com/lgw863/LogiQA-dataset/master/Test.txt",
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"en_eval": "https://raw.githubusercontent.com/lgw863/LogiQA-dataset/master/Eval.txt",
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}
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def _process_answer(answer):
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if not any(answer.startswith(x) for x in "ABCD"):
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return answer
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else:
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return answer[3:]
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def _process_sentences(text):
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text = text.replace("\n", "")
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sents = text.split(".")
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text = ""
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for sent in sents:
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if len(sent) == 0:
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continue
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if len(text) == 0:
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text += sent
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elif sent[0].isnumeric():
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text += "."+sent
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else:
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text += ". "+sent
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text = text.replace(" ", " ")
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text = text.replace("\\'", "'")
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while text.endswith(" "):
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text = text[:-1]
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if re.match('^[A-Z][\w\s]+[?.!]$', text) is None:
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text += "."
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text = text.replace("?.", "?")
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text = text.replace("!.", "!")
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text = text.replace("..", ".")
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return text
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class LogiQA(datasets.GeneratorBasedBuilder):
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def _info(self):
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features = datasets.Features(
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{
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"context": datasets.Value("string"),
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"query": datasets.Value("string"),
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"options": datasets.features.Sequence(datasets.Value("string")),
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"correct_option": datasets.Value("int32")
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}
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)
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return datasets.DatasetInfo(
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description=_DESCRIPTION,
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features=features,
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homepage=_HOMEPAGE,
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citation=_CITATION,
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)
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def _split_generators(self, dl_manager):
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downloaded_files = dl_manager.download_and_extract(_URLS)
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return [
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datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["en_train"]}),
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datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["en_eval"]}),
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datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["en_test"]}),
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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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logiqa = f.readlines()
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logiqa = [_process_sentences(s) for s in logiqa]
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for key in range(int(len(logiqa)/8)):
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row = 8*key
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correct_answer = logiqa[row+1].replace(".","")
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context = logiqa[row+2]
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query = logiqa[row+3]
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answers = logiqa[row+4:row+8]
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yield key, {
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"context": context,
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"query": query,
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"options": [_process_answer(answers[i]) for i in range(4)],
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"correct_option": "abcd".index(correct_answer)
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}
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