Improving Term Extraction with Terminological Resources

Sophie Aubin (1) , Thierry Hamon (1)

1 LIPN - Laboratoire d'Informatique de Paris-Nord

Studies of different term extractors on a corpus of the biomedical domain revealed decreasing performances when applied to highly technical texts. The difficulty or impossibility of customising them to new domains is an additional limitation. In this paper, we propose to use external terminologies to influence generic linguistic data in order to augment the quality of the extraction. The tool we implemented exploits testified terms at different steps of the process: chunking, parsing and extraction of term candidates. Experiments reported here show that, using this method, more term candidates can be acquired with a higher level of reliability. We further describe the extraction process involving endogenous disambiguation implemented in the term extractor YaTeA.

Mots clés: TAL; NLP; Acquisition terminologique; terminological knowledge acquisition; exploitation de ressources; extracteur de termes; term extractor; resources exploitation

Domaines: Informatique et langage [cs.CL]

Sophie Aubin, Thierry Hamon. Improving Term Extraction with Terminological Resources. 2006, pp.380. ⟨hal-00091444⟩