An empirical study on thematic knowledge acquisition based on syntactic clues and heuristics

  • Authors:
  • Rey-Long Liu;Von-Wun Soo

  • Affiliations:
  • National Tsing-Hua University, HsinChu, Taiwan, R.O.C.;National Tsing-Hua University, HsinChu, Taiwan, R.O.C.

  • Venue:
  • ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
  • Year:
  • 1993

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Abstract

Thematic knowledge is a basis of semantic interpretation. In this paper, we propose an acquisition method to acquire thematic knowledge by exploiting syntactic clues from training sentences. The syntactic clues, which may be easily collected by most existing syntactic processors, reduce the hypothesis space of the thematic roles. The ambiguities may be further resolved by the evidences either from a trainer or from a large corpus. A set of heuristics based on linguistic constraints is employed to guide the ambiguity resolution process. When a trainer is available, the system generates new sentences whose thematic validities can be justified by the trainer. When a large corpus is available, the thematic validity may be justified by observing the sentences in the corpus. Using this way, a syntactic processor may become a thematic recognizer by simply deriving its thematic knowledge from its own syntactic knowledge.