Knowledge extraction from machine-readable dictionaries: An evaluation
Identifieur interne : 000524 ( Main/Merge ); précédent : 000523; suivant : 000525Knowledge extraction from machine-readable dictionaries: An evaluation
Auteurs : Nancy Ide [France] ; Jean Véronis [États-Unis, France]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 1995.
Abstract
Abstract: Machine-readable versions of everyday dictionaries have been seen as a likely source of information for use in natural language processing because they contain an enormous amount of lexical and semantic knowledge. However, after 15 years of research, the results appear to be disappointing. No comprehensive evaluation of machine-readable dictionaries (MRDs) as a knowledge source has been made to date, although this is necessary to determine what, if anything, can be gained from MRD research. To this end, this paper will first consider the postulates upon which MRD research has been based over the past fifteen years, discuss the validity of these postulates, and evaluate the results of this work. We will then propose possible future directions and applications that may exploit these years of effort, in the light of current directions in not only NLP research, but also fields such as lexicography and electronic publishing.
Url:
DOI: 10.1007/3-540-59040-4_18
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<front><div type="abstract" xml:lang="en">Abstract: Machine-readable versions of everyday dictionaries have been seen as a likely source of information for use in natural language processing because they contain an enormous amount of lexical and semantic knowledge. However, after 15 years of research, the results appear to be disappointing. No comprehensive evaluation of machine-readable dictionaries (MRDs) as a knowledge source has been made to date, although this is necessary to determine what, if anything, can be gained from MRD research. To this end, this paper will first consider the postulates upon which MRD research has been based over the past fifteen years, discuss the validity of these postulates, and evaluate the results of this work. We will then propose possible future directions and applications that may exploit these years of effort, in the light of current directions in not only NLP research, but also fields such as lexicography and electronic publishing.</div>
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