Two Recent Developments in Tree Adjoining Grammars: Semantics and Efficient Processing

Abstract

ABSTRACT During the past year there have been two very significant developments in the area of Tree Adjoining Grammars (TAGs). The first development is a variant of TAGs, called synchronous TAGs, which allows TAG to be used beyond the confines of syntax by characterizing correspondences between languages. The formalism's intended usage is to relate expressions of natural languages to their associated semantics represented by a logical form language in TAG, or to their translates in another natural language. The formalism is incremental and inherently nondirectional. We will show by detailed examples the working of synchronous TAGs and some of its applications, for example in generation and in machine translation. The second development is the design of LR-style parsers for TAGs. LR parsing strategies evolved out of the original work of Knuth. Even though they are not powerful enough for NLP, they have found use in natural language processing 0VLP) by solving by pseudo-parallelism conflicts between multiple choices. This gives rise to a class of powerful yet efficient parsers for natural language. In order to extend the LR techniques to TAGs it is necessary to find bottom-up automaton that is exactly equivalent to TAGs. This is precisely what has been achieved by the discovery of the Bottom-up Embedded Push Down Automaton (BEPDA). Using BEPDA, deterministic left to fight parsers for the Tree Adjoining Languages have been developed.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 1990
Accession Number
ADA458891

Entities

People

  • Aravind K. Joshi
  • Yves Schabes

Organizations

  • University of Pennsylvania

Tags

DTIC Thesaurus Topics

  • Abstracts
  • Artificial Intelligence
  • Automata
  • Construction
  • Context Free Grammars
  • Demographic Cohorts
  • Grammars
  • Information Science
  • Language
  • Machine Translation
  • Machines
  • Natural Language Processing
  • Natural Languages
  • Semantics
  • Teamwork
  • Translations
  • Universities

Fields of Study

  • Computer science

Readers

  • Computational Linguistics

Technology Areas

  • AI & ML
  • AI & ML - Machine Translation