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Augmented Transition Network

Alias: ATN
  • Alan Bundy
  • Lincoln Wallen
Part of the Symbolic Computation book series (SYMBOLIC)

Abstract

Representation for grammars developed from simple finite state transition networks by allowing (a) recursion and (b) augmentation, i.e. the use of arbitrary tests and actions on arcs, giving full Turing machine power. The use of registers for storing constituents, and the use of tests and actions on register contents allow great flexibility in parsing, and in particular permit the construction of sentence representations quite distinct from the surface text e.g. deep as opposed to surface syntactic structures. The form of grammar representation is procedurally oriented, but the grammar itself is separated from the interpretive parser, which is top-down <248> and usually depth-first <55>. ATNs are a popular formalism and can be adapted e.g. to guide parsing by explicit arc ordering. Problems arise with e.g. passing information between subnets, and the treatment of conjunctions.

Keywords

Surface Text Great Flexibility Transition Network Syntactic Structure Register Content 
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.

Reference

  1. [Woods 70]
    Woods, W. A. Transition network grammars for natural language analysis. Communications of the ACM 13:591–606, 1970.Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1984

Authors and Affiliations

  • Alan Bundy
    • 1
  • Lincoln Wallen
  1. 1.Department of Artificial IntelligenceEdinburgh UniversityEdinburghScotland

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