Deep Read: a reading comprehension system

  • Authors:

  • Lynette Hirschman;Marc Light;Eric Breck;John D. Burger

  • Affiliations:

  • The MITRE Corporation, Bedford, MA;The MITRE Corporation, Bedford, MA;The MITRE Corporation, Bedford, MA;The MITRE Corporation, Bedford, MA

  • Venue:
  • ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
  • Year:
  • 1999

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Abstract

This paper describes initial work on Deep Read, an automated reading comprehension system that accepts arbitrary text input (a story) and answers questions about it. We have acquired a corpus of 60 development and 60 test stories of 3rd to 6th grade material; each story is followed by short-answer questions (an answer key was also provided). We used these to construct and evaluate a baseline system that uses pattern matching (bag-of-words) techniques augmented with additional automated linguistic processing (stemming, name identification, semantic class identification, and pronoun resolution). This simple system retrieves the sentence containing the answer 30--40% of the time.