By Fidelia Ibekwe-SanJuan, Anne Condamines, M. Teresa Cabre Castellvi
A typical framework below which a few of the experiences on terminology processing should be considered is to think about not just the texts from which the terminological assets are equipped yet relatively the functions specified. the present ebook, first released as a distinct factor of Terminology 11:1 (2005), analyses the effect of purposes on time period definition and processing. different types of purposes were pointed out: middleman and terminal functions (involving finish users). middleman functions drawback the development of terminological wisdom assets comparable to domain-specific dictionaries, ontologies, word list or taxonomies. those wisdom assets then shape the inputs to terminal purposes comparable to info extraction, details retrieval, technology and expertise watch or computerized e-book index development. lots of the purposes handled within the booklet fall into the 1st class. This ebook represents the 1st try, from a pluridisciplinary standpoint, take into consideration the position of functions within the processing of terminology.
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Additional resources for Application-driven terminology engineering
In Chaurand, J. and F. ). La définition. 86–95. Paris: Larousse. Meyer, I. 2001. , C. C. ). Recent advances in Computational Terminology. 279– 302. Amsterdam/Philadephia: John Benjamins. Morin, E. 1998. ” In Traitement automatique du langage naturel (TALN 1998). 172–191. Paris, France. Muresan, S. and J. Klavans. 2002. ” In Language Ressources and Evaluation Conference (LREC 2002). 231–234. Las Palmas, Spain. Pearson, J. 1999. ” In Terminologie et intelligence artificielle (TIA 1999). 21–38. Nantes, France.
Lexico-syntactic patterns are a relevant methodology to mine defining contexts in corpora, which enables the system to point out pairs of related terms, and to propose a number of potential relations between these terms. Once the semantic relation is validated, the pair of terms can be structured: if they are co-hyponyms, they stand at the same ontological level, if they are hyponymous, they have a hierarchical dependence. This “node level” structuring can be a first step in ontology modelling.
3 Multi-term and multi-sentence defining contexts Embedded defining contexts can be of different kinds: there can be definitions of different terms in the same sentence (5), a definition in separate parts (6), a definition inside another one (7), and the association of different terms with the same hypernym in one sentence (8). The underlined parts in the examples below are the main terms of the defining context, the terms in italics in example (7) are also the main terms of the same defining context.