Resolving complex cases of definite pronouns: the winograd schema challenge

  • Authors:
  • Altaf Rahman;Vincent Ng

  • Affiliations:
  • University of Texas at Dallas, Richardson, TX;University of Texas at Dallas, Richardson, TX

  • Venue:
  • EMNLP-CoNLL '12 Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning
  • Year:
  • 2012

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Abstract

We examine the task of resolving complex cases of definite pronouns, specifically those for which traditional linguistic constraints on coreference (e.g., Binding Constraints, gender and number agreement) as well as commonly-used resolution heuristics (e.g., string-matching facilities, syntactic salience) are not useful. Being able to solve this task has broader implications in artificial intelligence: a restricted version of it, sometimes referred to as the Winograd Schema Challenge, has been suggested as a conceptually and practically appealing alternative to the Turing Test. We employ a knowledge-rich approach to this task, which yields a pronoun resolver that outperforms state-of-the-art resolvers by nearly 18 points in accuracy on our dataset.