By Fidelia Ibekwe-SanJuan, Anne Condamines, M. Teresa Cabre Castellvi

A standard framework less than which many of the experiences on terminology processing might be seen is to contemplate not just the texts from which the terminological assets are outfitted yet really the functions specific. the present publication, first released as a different factor of Terminology 11:1 (2005), analyses the impact of functions on time period definition and processing. forms of functions were pointed out: middleman and terminal purposes (involving finish users). middleman functions predicament the construction of terminological wisdom assets reminiscent of domain-specific dictionaries, ontologies, word list or taxonomies. those wisdom assets then shape the inputs to terminal functions corresponding to info extraction, info retrieval, technology and expertise watch or computerized booklet index development. lots of the functions handled within the publication fall into the 1st type. This ebook represents the 1st try out, from a pluridisciplinary perspective, take into consideration the position of purposes within the processing of terminology.

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To name), dénoter (Engl. to denote), designer (Engl. to designate), nommer (Engl. to name), signifier (Engl. to signify), vouloir dire (Engl. to mean); – patterns based on 12 nominal metalinguistic markers (appellation, acception, concept, définition, dénomination, désignation, expression, mot (Engl. word), nom (Engl. name), notion, terme, vocable), to be combined with the associated verbs: appliquer (Engl. to apply), donner (Engl. to give), employer (Engl. to use), prendre (Engl. to take), porter (Engl.

Bébé 41 42 Véronique Malaisé, Pierre Zweigenbaum and Bruno Bachimont Therefore we have associated a relevance measure to each term on the basis of its frequency in defining contexts: the more often a word is present, the less it is relevant to connect terms. idf measure to calculate it,17 and performed a hierarchical agglomerative clustering on a matrix derived from the similarity table: each row of this matrix is a term defined in the corpus sharing at least one word with another term in its defining context, and each colomn represents the words shared by at least two defining contexts (Table 11).

For instance, a parenthesis can introduce defining contexts of hypernymic, synonymic or functional types, or some other interesting contexts which links terms likely to be ontology siblings. But each pattern specifies a more constraining context for which it is more likely that one particular relation occurs. This specific relation was determined on the basis of the human analysis of a sample of the test corpus. 4 Implementation The parsed corpus is converted to an XML document. Lexico-syntactic patterns are described by XSLT templates which are applied to the corpus.

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