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Generating paraphrases from meaning‐text semantic networks

 

作者: Michel Boyer,   Guy Lapalme,  

 

期刊: Computational Intelligence  (WILEY Available online 1985)
卷期: Volume 1, issue 1  

页码: 103-117

 

ISSN:0824-7935

 

年代: 1985

 

DOI:10.1111/j.1467-8640.1985.tb00063.x

 

出版商: Blackwell Publishing Ltd

 

关键词: sentence generation;generalized unification;Prolog;semantic networks;meaning‐text model

 

数据来源: WILEY

 

摘要:

This paper describes a first attempt to base a paraphrase generation system upon Meľčuk and Žolkovskij's linguistic meaning‐text (MT) model whose purpose is to establish correspondences between meanings, represented by networks, and (ideally) all synonymous texts having this meaning. The system described here contains a Prolog implementation of a small explanatory and combinatorial dictionary (the MT lexicon) and, using unification and backtracking, generates from a given network the sentences allowed by the dictionary and the lexical transformations of the model. The passage from a net to the final texts is done through a series of transformations of intermediary structures that closely correspond to MT utterance representations (semantic, deep‐syntax, surface‐syntax, and morphological representations). These are graphs and trees with labeled arcs. The Prolog unification (equality predicate) was extended to extract information from these representations and build new ones. The notion of utterance path, used by many authors, is replaced by that ofcovering by defining sub

 

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