title: From syntactic-semantic tagging to knowledge discovery in medical texts.
abstract: In the GALEN project, the syntactic-semantic tagger MultiTALE is upgraded to extract knowledge from natural language surgical procedure expressions. In this paper, we describe the methodology applied and show that out of a randomly selected sample of such expressions coming from the procedure axis of Snomed International, 81% could be analysed correctly. The problems encountered fall in three different categories: unusual grammatical configurations within the Snomed terms, insufficient domain knowledge and different categorisation of concepts and semantic links in the domain and linguistic models used. It is concluded that the Multi-TALE system can be used to attach meaning to words that not have been encountered previously, but that an interface ontology mediating between domain models and linguistic models is needed to arrive at a higher level of independence from both particular languages and from particular domains.
authors.affiliation: Language and Computing NV, Het Moorhof, Zonnegem, Belgium. werner.ceusters@rug.ac.be
authors.forename: W
authors.initials: W
authors.lastname: Ceusters
authors.forename: P
authors.initials: P
authors.lastname: Spyns
authors.forename: G
authors.initials: G
authors.lastname: De Moor
mesh_terms: D005544:Forecasting; D006801:Humans; D008037:Linguistics; D009323:Natural Language Processing; D019635:Neurosurgical Procedures; D012660:Semantics; D009626:Terminology as Topic