C³

Overview

This repository maintains C³, the first free-form multiple-Choice Chinese machine reading Comprehension dataset.

• Paper: https://arxiv.org/abs/1904.09679

@article{sun2019investigating,
  title={Investigating Prior Knowledge for Challenging Chinese Machine Reading Comprehension},
  author={Sun, Kai and Yu, Dian and Yu, Dong and Cardie, Claire},
  journal={Transactions of the Association for Computational Linguistics},
  year={2020},
  url={https://arxiv.org/abs/1904.09679v3}
}

Files in this repository:

• license.txt: the license of C³.
• data/c3-{m,d}-{train,dev,test}.json: the dataset files, where m and d represent "mixed-genre" and "dialogue", respectively. The data format is as follows.

[
  [
    [
      document 1
    ],
    [
      {
        "question": document 1 / question 1,
        "choice": [
          document 1 / question 1 / answer option 1,
          document 1 / question 1 / answer option 2,
          ...
        ],
        "answer": document 1 / question 1 / correct answer option
      },
      {
        "question": document 1 / question 2,
        "choice": [
          document 1 / question 2 / answer option 1,
          document 1 / question 2 / answer option 2,
          ...
        ],
        "answer": document 1 / question 2 / correct answer option
      },
      ...
    ],
    document 1 / id
  ],
  [
    [
      document 2
    ],
    [
      {
        "question": document 2 / question 1,
        "choice": [
          document 2 / question 1 / answer option 1,
          document 2 / question 1 / answer option 2,
          ...
        ],
        "answer": document 2 / question 1 / correct answer option
      },
      {
        "question": document 2 / question 2,
        "choice": [
          document 2 / question 2 / answer option 1,
          document 2 / question 2 / answer option 2,
          ...
        ],
        "answer": document 2 / question 2 / correct answer option
      },
      ...
    ],
    document 2 / id
  ],
  ...
]

• annotation/c3-{m,d}-{dev,test}.txt: question type annotations. Each file contains 150 annotated instances. We adopt the following abbreviations:

	Abbreviation	Question Type
Matching	m	Matching
Prior knowledge	l	Linguistic
	s	Domain-specific
	c-a	Arithmetic
	c-o	Connotation
	c-e	Cause-effect
	c-i	Implication
	c-p	Part-whole
	c-d	Precondition
	c-h	Scenario
	c-n	Other
Supporting Sentences	0	Single Sentence
	1	Multiple sentences
	2	Independent