By Fidelia Ibekwe-SanJuan, Anne Condamines, M. Teresa Cabre Castellvi
A standard framework less than which a number of the reports on terminology processing will be considered is to contemplate not just the texts from which the terminological assets are equipped yet relatively the purposes designated. the present publication, first released as a unique factor of Terminology 11:1 (2005), analyses the impression of purposes on time period definition and processing. forms of functions were pointed out: middleman and terminal functions (involving finish users). middleman purposes quandary 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 functions akin to info extraction, details retrieval, technological know-how and know-how watch or computerized booklet index development. many of the purposes handled within the ebook fall into the 1st class. This ebook represents the 1st test, from a pluridisciplinary point of view, take into consideration the position of functions within the processing of terminology.
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Extra resources for Application-driven terminology engineering
3% on the evaluation corpus. The recall scores are higher than those of previous tests in Malaisé et al. (2004) which were respectively 35 36 Véronique Malaisé, Pierre Zweigenbaum and Bruno Bachimont Figure 3. Precision evaluation categories 4% and 36% on the evaluation corpus), because we added very productive markers and patterns to the system (the “is_a” marker for instance). There is still room for improvement by adding other punctuation signs as markers (dash and colon for instance). Precision is shown on Tables 4 and 5.
2 Extraction of the main terms In order to help an ontology modeller in his task, we need to extract at least the definiendum from the general defining context: we need to present the modeller with the main defined term of the defining sentence(s). We also need to extract the definiendum to integrate it automatically in the ontology. 3). This is the reason why we extract not only the definiendum, but two “main terms”. What we mean with the “main terms” is linked with the characterisation of defining contexts that we have presented in Section 3: Term1 related_to (Term2?
Depending on the semantic relation, the terms will have different respective positions in the hierarchical tree. They will have to be integrated at different ontology levels if they are hypernym and hyponym, and be related to the same label if they are synonyms. As mentioned above, we focus on hypernymy and synonymy detection in defining contexts. 3 Identification of the semantic relation We have seen in the typology presented in Tables 1 and 2 that different semantic relations can be found in defining contexts.