PDF] Reconciling fine-grained lexical knowledge and coarse-grained ontologies in the representation of near-synonyms

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.

PDF) Experiments on Extracting Knowledge from a Machine-Readable Dictionary of Synonym Differences

Morpho-lexical Issues in Chinese (Part Two) - The Cambridge Handbook of Chinese Linguistics

PDF) Reconciling Fine-Grained Lexical Knowledge and Coarse-Grained Ontologies in the Representation of Near-Synonyms

Ontology and the Lexicon

Viewpoints which Matter – Philosophy, Psychology, Ecology, Sociology, Economics, Finance, Strategy, Scenarios, Futures, Foresight, Operational Research, Complexity, Networks, Systems

Experiments on Extracting Knowledge from a Machine-Readable Dictionary of Synonym Differences

IJGI, Free Full-Text

The Philosophy of Humanism by CEC School of Theology in Europe - Issuu

A generic metamodel for data extraction and generic ontology population - Yohann Chasseray, Anne-Marie Barthe-Delanoë, Stéphane Négny, Jean-Marc Le Lann, 2022

Morpho-lexical Issues in Chinese (Part Two) - The Cambridge Handbook of Chinese Linguistics

PDF] Near-synonymy and the structure of lexical knowledge

Global pathways to knowledge: narration and translation