Terminology Encoding in View of Multifunctional NLP Resources

Abstract

Given the existing standards for organising terminology resources, the main question raised is how to create a DB or assimilated term list with properties allowing for an efficient NLP treatment of input texts. Here, we have dealt with the output of MT and have attempted to improve terminological annotation of the input text, in order to optimize reusability and efficiency of performance. By organizing terms in BD-like tables, which provide various cross-linked indications about head properties, morpho-syntax, derivational morphology and semantic-pragmatic relations between concepts of terms, we have managed to improve functionality of resources and enable better customisation. Moreover, we have tried to view the proposed term DB organisation as part of a global account of the problem of terminology resolution on-processing via grammar based or user-machine interaction techniques for term recognition and disambiguation, since term boundary definition is generally recognised to be a complex and costly enterprise, directly related to the fact that most problem causing terminology items are multi-word units either characterized as fixed or as ad hoc or not yet fixed terms.

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