COGPARSE: Brain-Inspired Knowledge-Driven Full Semantics Parsing

Radical Construction Grammar, Categories, Knowledge-Based Parsing & Representation
  • Daniel J. Olsher
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7366)

Abstract

Humans use semantics during parsing; so should computers. In contrast to phrase structure-based parsers, COGPARSE seeks to determine which meaning-bearing components are present in a text, using world knowledge and lexical semantics for construction grammar form selection, syntactic overlap processing, disambiguation, and confidence calculation. In a brain-inspired way, COGPARSE aligns parsing with the structure of the lexicon, providing a linguistic representation, parsing algorithm, associated linguistic theory, and preliminary metrics for evaluating parse quality. Given sufficient information on nuanced word and construction semantics, COGPARSE can also assemble detailed full-semantics meaning representations of input texts. Beyond the ability to determine which parses are most likely to be intended and to use knowledge in disambiguation, full-semantics parsing enables nuanced meaning representation, learning, summarization, natural language user interfaces, and the taking of action based on natural language input.

Keywords

Lexical Item Semantic Type Input Text World Knowledge Defense Advance Research Project Agency 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Daniel J. Olsher
    • 1
  1. 1.Cognitive Science Program, Temasek LaboratoriesNational University of SingaporeSingapore

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