Grammatical Trigrams: A Probabilistic Model of Link Grammar

Abstract

In this paper we present a new class of language models. This class derives from link grammar a context-free formalism for the description of natural language. We describe an algorithm for determining maximum-likelihood estimates of the parameters of these models. The language models which we present differ from previous models based on stochastic context-free grammars in that they are highly lexical. In particular they include the familiar n-gram models as a natural subclass The motivation for considering this class is to estimate the contribution which grammar can make to reducing the relative entropy of natural language.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1992
Accession Number
ADA256365

Entities

People

  • Davy Temperley
  • John D. Lafferty
  • Saniel Sleator

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Energy and Power Technologies

DTIC Thesaurus Topics

  • Algorithms
  • Computations
  • Computer Science
  • Connectors
  • Dynamic Programming
  • Generative Models
  • Grammars
  • Language
  • Models
  • Natural Languages
  • Phrase Structure Grammars
  • Probabilistic Models
  • Probability
  • Random Variables

Fields of Study

  • Computer science

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computational Linguistics