An interlingual-based approach to reference resolution

  • Authors:
  • David Farwell;Stephen Helmreich

  • Affiliations:
  • New Mexico State University, Las Cruces, New Mexico;New Mexico State University, Las Cruces, New Mexico

  • Venue:
  • NAACL-ANLP-Interlinguas '00 Proceedings of the 2000 NAACL-ANLP Workshop on Applied interlinguas: practical applications of interlingual approaches to NLP - Volume 2
  • Year:
  • 2000

Quantified Score

Hi-index 0.00

Visualization

Abstract

In this paper we outline an interlingual-based procedure for resolving reference and suggest a practical approach to implementing it. We assume a two-stage language analysis system. First, a syntactic analysis of an input text results in a functional structure in which certain cases of pronominal reference are resolved. Second, the f-structure is mapped onto an interlingual representation. As part of this mapping, the reference of the various f-structure elements is resolved resulting in the addition of information to certain existing IL objects (coreference) or in the creation of new IL objects which are added to the domain of discourse (initial reference).For this effort, we adopt Text Meaning Representation for our IL and rely on the ONTOS ontology (Mahesh & Nirenburg, 1995) as a general knowledge base. Since the central barrier to developing such a system today is the incompleteness of the knowledge base, we outline a strategy starting with the implementation of a series of form-based resolution algorithms that are applied directly to the referring expressions of the input text. These are initially supplemented by a knowledge-based resolution procedure which, as the knowledge base grows and the adequacy of the f-structure and IL-representation increases, takes on more and more of the processing load.We examine the operation of the form-based algorithms on a sample Spanish text and show their limitations. We then demonstrate how an IL-based approach can be used to resolve the problematic cases of reference. This research effort is part of the CREST project at the CRL funded by DARPA.