Predicting Lexical Relations between Biomedical Terms: towards a Multilingual Morphosemantics-based System.
This paper addresses the issue of how semantic information can be automatically assigned to compound terms, i.e. both a definition and a set of semantic relations. This issue is particularly crucial when elaborating multilingual databases and when developing cross-language information retrieval systems. The paper shows how morpho-semantics can contribute in the constitution of multilingual lexical networks in biomedical corpora. It presents a system capable of labelling terms with morphologically related words, i.e. providing them with a definition, and grouping them according to synonymy, hyponymy and proximity relations. The approach requires the interaction of three techniques: (1) a la morphosemantic parser, (2) a multilingual table defining basic relations between word roots, and (3) a set of language-independant rules to draw up the list of related terms. This approach has been fully implemented for French, on an about 29,000 terms biomedical lexicon, resulting to more than 3,000 lexical families.
Namer
Fiammetta
F
UMR ATILF CNRS & University of Nancy2, Nancy, France. Fiammetta.Namer@univ-nancy2.fr
Baud
Robert
R
D007802:Language; D019303:Multilingualism; D009323:Natural Language Processing; D012660:Semantics; D017432:Unified Medical Language System