Recovering Implicit Information

  • Martha S. Palmer
  • Deborah A. Dahl
  • Rebecca J. Schiffman
  • Lynette Hirschman
  • Marcia Linebarger
  • John Dowding
Part of the Linguistica Computazionale book series (LICO, volume 9)


This paper describes the SDC PUNDIT (Prolog UNDerstands Integrated Text), system for processing natural language messages. PUNDIT, written in Prolog, is a highly modular system consisting of distinct syntactic, semantic and pragmatics components. Each component draws on one or more sets of data, including a lexicon, a broad-coverage grammar of English, semantic verb decompositions, rules mapping between syntactic and semantic constituents, and a domain model.

This paper discusses the communication between the syntactic, semantic and pragmatic modules that is necessary for making implicit linguistic information explicit. The key is letting syntax and semantics recognize missing linguistic entities as implicit entities, so that they can be labeled as such, and reference resolution can be directed to find specific referents for the entities. In this way the task of making implicit linguistic information explicit becomes a subset of the tasks performed by reference resolution. The success of this approach is dependent on marking missing syntactic constituents as elided and missing semantic roles as ESSENTIAL so that reference resolution can know when to look for referents.


Noun Phrase Disk Drive Mapping Rule Semantic Role Spindle Motor 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media Dordrecht 1994

Authors and Affiliations

  • Martha S. Palmer
    • 1
  • Deborah A. Dahl
    • 1
  • Rebecca J. Schiffman
    • 1
  • Lynette Hirschman
    • 1
  • Marcia Linebarger
    • 1
  • John Dowding
    • 1
  1. 1.R&DSDC — A Burroughs CompanyUSA

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