Abstract
DEFI is a prototype computer tool aimed at ranking (from most to least relevant) the French translations of an English lexical item in context. This paper deals with the strategies used by DEFI to recognize multi-word units (mwus) in running text. Any lexical unit included in the lexical database used in the project (a merge of the Oxford/Hachette and Robert/Collins English-to-French dictionaries) and longer than a single word is submitted to a surface parser, and the same process is applied to the user ’s text. A program written in Prolog assesses the quality of the match between the parsed user’s text and candidate mwus retrieved from the project’s lexical database. The matcher is able to account for some of the distortions undergone by the mwu, e.g. movement of a constituent as a result of relativization or passivization.
Highlights
DEFI is a prototype computer tool aimed at ranking the French translations of an English lexical item in context
This paper deals with the strategies used by
Any lexical unit included in the lexical database used in the project
Summary
DEFI is a prototype computer tool aimed at ranking (from most to least relevant) the French translations of an English lexical item in context. Quel que soit le soin que l’on apporte à décrire les contextes qui supportent la lexie et les manipulations dont elle peut faire l’objet, on ne pourra pas faire l’économie d’un recours au sens, au vouloir dire, lequel ne se laisse pas réduire à des corrélats linguistiques observables, en dépit de notre intuition persistante que ce devrait être le cas puisque après tout le lecteur humain ne dispose lui aussi que du texte. DEFI, par son système de pondération, privilégiera les manifestations textuelles qui sont les plus proches des lexies telles que présentées par les deux dictionnaires, à savoir: to have a free hand to have a free hand to do sth to give sb a free hand Mais il est tout prêt à ‘sauter’ (silent move) le couple to+have en tête des deux premières lexies, et il admettra que le déterminant a soit apparié à un autre élément du même type. Cette attitude n’a de sens que si l’utilisateur est un utilisateur humain, qui ne fait appel à l’appariement en mode -m que si la lecture compositionnelle lui paraît bizarre ou insuffisante
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