MC-Test Dataset

A MC-Test Dataset is a reading comprehension dataset that contains set of stories and questions for research on the machine comprehension of texts.

• Context:
  • It was developed by Richardson et al. (2013).
• Example(s):
  • MC160 Dataset,
  • MC500 Dataset.
  • …
• Counter-Example(s):
  • a BookTest Dataset,
  • a Children's Book Test (CBT) Dataset,
  • a CNN-Daily Mail Dataset,
  • a MS MARCO Dataset,
  • a RACE Dataset.
  • an Image Description Dataset.
• See: Question-Answering System, Question-Answer Dataset, Natural Language Processing Task, Natural Language Understanding Task, Natural Language Generation Task.

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References

2013

• (Richardson et al., 2013) ⇒ Matthew Richardson, Christopher J. C. Burges, and Erin Renshaw. (2013). “MCTest: A Challenge Dataset for the Open-Domain Machine Comprehension of Text.” In: Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing (EMNLP 2013). A meeting of SIGDAT, a Special Interest Group of the ACL.
  • QUOTE: We present MCTest, a freely available set of stories and associated questions intended for research on the machine comprehension of text. Previous work on machine comprehension (e.g., semantic modeling) has made great strides, but primarily focuses either on limited-domain datasets, or on solving a more restricted goal (e.g., open-domain relation extraction). In contrast, MCTest requires machines to answer multiple-choice reading comprehension questions about fictional stories, directly tackling the high-level goal of open-domain machine comprehension.

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