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- 514 creator mehdi-embarek.
- 514 creator olivier-ferret.
- 514 type InProceedings.
- 514 label "Learning Patterns for Building Resources about Semantic Relations in the Medical Domain".
- 514 sameAs 514.
- 514 abstract "In this article, we present a method for extracting automatically semantic relations from texts in the medical domain using linguistic patterns. These patterns refer to three levels of information about words: inflected form, lemma and part-of-speech. The method we present consists first in identifying the entities that are part of the relations to extract, that is to say diseases, exams, treatments, drugs or symptoms. Thereafter, sentences that contain couples of entities are extracted and the presence of a semantic relation is validated by applying linguistic patterns. These patterns were previously learnt automatically from a manually annotated corpus by relying onan algorithm based on the edit distance. We first report the results of an evaluation of our medical entity tagger for the five types of entities we have mentioned above and then, more globally, the results of an evaluation of our extraction method for four relations between these entities. Both evaluations were done for French.".
- 514 hasAuthorList authorList.
- 514 hasTopic Linguistics.
- 514 isPartOf proceedings.
- 514 keyword "Acquisition, Machine Learning".
- 514 keyword "Ontologies".
- 514 keyword "Semantics".
- 514 title "Learning Patterns for Building Resources about Semantic Relations in the Medical Domain".