Accession Number:

ADA458651

Title:

Lexical Selection for Cross-Language Applications: Combining LCS with WordNet

Descriptive Note:

Technical rept.

Corporate Author:

MARYLAND UNIV COLLEGE PARK INST FOR ADVANCED COMPUTER STUDIES

Personal Author(s):

Report Date:

1998-10-01

Pagination or Media Count:

12.0

Abstract:

This paper describes experiments for testing the power of large-scale resources for lexical selection in machine translation NIT and cross-language information retrieval CLIR. We adopt the view that verbs with similar argument structure share certain meaning components, but that those meaning components are more relevant to argument realization than to idiosyncratic verb meaning. We verify this by demonstrating that verbs with similar argument structure as encoded in Lexical Conceptual Structure LCS are rarely synonymous in WordNet. We then use the results of this work to guide our implementation of an algorithm for cross-language selection of lexical items, exploiting the strengths of each resource LCS for semantic structure and WordNet for semantic content. We use the Parka Knowledge-Based System to encode LCS representations and WordNet synonym sets and we implement our lexical-selection algorithm as Parka-based queries into a knowledge base containing both information types.

Subject Categories:

  • Linguistics
  • Computer Programming and Software
  • Operations Research

Distribution Statement:

APPROVED FOR PUBLIC RELEASE