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README.md

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----
-task_categories:
-- question-answering
-language:
-- zh
-pretty_name: LogiQA-zh
-size_categories:
-- 1K<n<10K
-paperswithcode_id: logiqa
-dataset_info:
-  features:
-  - name: context
-    dtype: string
-  - name: query
-    dtype: string
-  - name: options
-    sequence:
-      dtype: string
-  - name: correct_option
-    dtype: string
-  splits:
-  - name: train
-    num_examples: 7376
-  - name: validation
-    num_examples: 651
-  - name: test
-    num_examples: 651
----
-# Dataset Card for LogiQA
-
-## Dataset Description
-
-- **Homepage:** 
-- **Repository:** 
-- **Paper:** 
-- **Leaderboard:** 
-- **Point of Contact:** 
-
-### Dataset Summary
-
-LogiQA is constructed from the logical comprehension problems from publically available questions of the National Civil Servants Examination of China, which are designed to test the civil servant candidates’ critical thinking and problem solving. This dataset includes the Chinese versions only.
-
-
-## Dataset Structure
-
-### Data Instances
-
-An example from `train` looks as follows:
-```
-{'context': '有些广东人不爱吃辣椒.因此,有些南方人不爱吃辣椒.',
- 'query': '以下哪项能保证上述论证的成立？',
- 'options': ['有些广东人爱吃辣椒',
-  '爱吃辣椒的有些是南方人',
-  '所有的广东人都是南方人',
-  '有些广东人不爱吃辣椒也不爱吃甜食'],
- 'correct_option': 2}
-```
-
-### Data Fields
-
-- `context`: a `string` feature.
-- `query`: a `string` feature.
-- `answers`: a `list` feature containing `string` features.
-- `correct_option`: a `string` feature.
-
-
-### Data Splits
-
-|train|validation|test|
-|----:|---------:|---:|
-| 7376|       651| 651|
-
-
-## Additional Information
-
-### Dataset Curators
-
-The original LogiQA was produced by Jian Liu, Leyang Cui , Hanmeng Liu, Dandan Huang, Yile Wang, and Yue Zhang.
-
-### Licensing Information
-
-[More Information Needed]
-
-### Citation Information
-
-```
-@article{liu2020logiqa,
-  title={Logiqa: A challenge dataset for machine reading comprehension with logical reasoning},
-  author={Liu, Jian and Cui, Leyang and Liu, Hanmeng and Huang, Dandan and Wang, Yile and Zhang, Yue},
-  journal={arXiv preprint arXiv:2007.08124},
-  year={2020}
-}
-```
-
-### Contributions
-[@jiacheng-ye](https://github.com/jiacheng-ye) added this Chinese dataset.
-[@lucasmccabe](https://github.com/lucasmccabe) added the English dataset.

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default/logiqa-zh-train.parquet

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logiqa-zh.py

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-"""LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning"""
-
-import re
-import datasets
-
-logger = datasets.logging.get_logger(__name__)
-
-
-_HOMEPAGE = "https://github.com/lgw863/LogiQA-dataset"
-
-_DESCRIPTION = """\
-LogiQA is constructed from the logical comprehension problems from \
-publically available questions of the National Civil Servants Examination \
-of China, which is designed to test the civil servant candidates’ critical \
-thinking and problem-solving. This dataset includes the Chinese versions only"""
-
-_CITATION = """\
-@article{liu2020logiqa,
-  title={Logiqa: A challenge dataset for machine reading comprehension with logical reasoning},
-  author={Liu, Jian and Cui, Leyang and Liu, Hanmeng and Huang, Dandan and Wang, Yile and Zhang, Yue},
-  journal={arXiv preprint arXiv:2007.08124},
-  year={2020}
-}
-"""
-
-_URLS = {
-    "zh_train": "https://raw.githubusercontent.com/lgw863/LogiQA-dataset/master/zh_train.txt",
-    "zh_test": "https://raw.githubusercontent.com/lgw863/LogiQA-dataset/master/zh_test.txt",
-    "zh_eval": "https://raw.githubusercontent.com/lgw863/LogiQA-dataset/master/zh_eval.txt",
-}
-
-def _process_answer(answer):
-    if not any(answer.startswith(x) for x in "ABCD"):
-        return answer
-    else:
-        return answer[3:]
-
-def _process_sentences(text):
-    text = text.replace("\n", "")
-    sents = text.split(".")
-    text = ""
-    for sent in sents:
-        if len(sent) == 0:
-            continue
-        if len(text) == 0:
-            text += sent
-        elif sent[0].isnumeric():
-            text += "."+sent
-        else:
-            text += ". "+sent
-    text = text.replace("  ", " ")
-    text = text.replace("\\'", "'")
-    while text.endswith(" "):
-        text = text[:-1]
-    if re.match('^[A-Z][\w\s]+[?.!]$', text) is None:
-        text += "."
-    text = text.replace("?.", "?")
-    text = text.replace("!.", "!")
-    text = text.replace("..", ".")
-    return text
-
-class LogiQA(datasets.GeneratorBasedBuilder):
-    def _info(self):
-        features = datasets.Features(
-            {
-                "context": datasets.Value("string"),
-                "query": datasets.Value("string"),
-                "options": datasets.features.Sequence(datasets.Value("string")),
-                "correct_option": datasets.Value("int32")
-            }
-        )
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=features,
-            homepage=_HOMEPAGE,
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        downloaded_files = dl_manager.download_and_extract(_URLS)
-        return [
-            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["zh_train"]}),
-            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["zh_eval"]}),
-            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["zh_test"]}),
-        ]
-
-    def _generate_examples(self, filepath):
-        logger.info("generating examples from = %s", filepath)
-        with open(filepath, encoding="utf-8") as f:
-            logiqa = f.readlines()
-            logiqa = [_process_sentences(s) for s in logiqa]
-
-            for key in range(int(len(logiqa)/8)):
-                row = 8*key
-                correct_answer = logiqa[row+1].replace(".","")
-                context = logiqa[row+2]
-                query = logiqa[row+3]
-                answers = logiqa[row+4:row+8]
-
-                yield key, {
-                    "context": context,
-                    "query": query,
-                    "options": [_process_answer(answers[i]) for i in range(4)],
-                    "correct_option": "abcd".index(correct_answer)
-                }