Learning structural descriptions of grammar rules from examples

  • Authors:
  • Robert C. Berwick

  • Affiliations:
  • Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, Massachusetts

  • Venue:
  • IJCAI'79 Proceedings of the 6th international joint conference on Artificial intelligence - Volume 1
  • Year:
  • 1979

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Abstract

This paper describes a LISP program that can learn English syntactic rules The key idea is that the learning can be made easy, given the right initial computational structure: syntactic knowledge is separated into a fixed mterpicter and a variable set of highly constrained pattern-action grammar rules Only the grammar rules are learned, via induction from example sentences presented to the program. The interpreter is a simplified version of Marcus's parser for English [I], which parses sentences without backup. The currently implemented program acquires about 707 of a simplified core grammar of English What seems to make the induction easy is that the rule structures and their actions are highly constrained: there are only four actions, and they manipulate only very local parts of the parse tree.