The Simple Language Generator: Encoding Complex Languages With Simple Grammars

Abstract

This paper introduces the design and use of the Simple Language Generator (SLG). SLG allows the user to construct small but interesting stochastic context free languages with relative ease. Although context free grammars are convenient for representing natural language syntax, they do not easily support the semantic and pragmatic constraints that make certain combinations of words or structures more likely than others. Context free grammars for languages involving many interacting constraints can become extremely complex and cannot reasonably be written by hand. SLG allows the basic syntax of a grammar to be specified in context free form and constraints to be applied atop this framework in a relatively natural fashion. This combination of grammar and constraints is then converted into a standard stochastic context free grammar for use in generating sentences or in making context dependent likelihood predictions of the sequence of words in a sentence.

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Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1999
Accession Number
ADA368421

Entities

People

  • Douglas L. T. Rohde

Organizations

  • Carnegie Mellon University

Tags

Communities of Interest

  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Computer Science
  • Context Free Grammars
  • Embedding
  • Filters
  • Grammars
  • Hidden Markov Models
  • Language
  • Machine Learning
  • Markov Models
  • Models
  • Natural Languages
  • Neural Networks
  • Notation
  • Probability
  • Standards
  • Symbols

Fields of Study

  • Linguistics

Readers

  • Computational Linguistics