PDF] Reconciling fine-grained lexical knowledge and coarse-grained ontologies in the representation of near-synonyms
Por um escritor misterioso
Last updated 30 março 2025
![PDF] Reconciling fine-grained lexical knowledge and coarse-grained ontologies in the representation of near-synonyms](https://d3i71xaburhd42.cloudfront.net/58205df22e7dba90a8f0deaa1a1b9c5447e409d0/2-Table1-1.png)
A new model for representing fine-grained lexical knowledge whose basis is the idea of granularity of representation is discussed. A machine translation system must be able to adequately cope with near-synonymy for there are often many slightly different translations available for any given source language word that can each significantly and differently affect the meaning or style of a translated text. Conventional models of lexical knowledge used in natural-language processing systems are inadequate for representing near-synonyms, because they are unable to represent fine-grained lexical knowledge. We will discuss a new model for representing fine-grained lexical knowledge whose basis is the idea of granularity of representation.
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PDF] Near-synonymy and the structure of lexical knowledge
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PDF) Reconciling Fine-Grained Lexical Knowledge and Coarse-Grained Ontologies in the Representation of Near-Synonyms
![PDF] Reconciling fine-grained lexical knowledge and coarse-grained ontologies in the representation of near-synonyms](https://media.springernature.com/m685/springer-static/image/art%3A10.1038%2Fs41746-019-0162-5/MediaObjects/41746_2019_162_Fig2_HTML.png)
Enabling Web-scale data integration in biomedicine through Linked Open Data
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Chapter 4 Tracing Materialities of the Mental through Ulyssean Minds in: Modernist Minds
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Ontology Learning Using Word Net Lexical Expansion and Text Mining
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