Paper: DALE: A Word Sense Disambiguation System for Biomedical Documents Trained using Automatically Labeled Examples

ACL ID N13-3001
Title DALE: A Word Sense Disambiguation System for Biomedical Documents Trained using Automatically Labeled Examples
Venue Annual Conference of the North American Chapter of the Association for Computational Linguistics
Session System Demonstration
Year 2013
Authors

Automatic interpretation of documents is hampered by the fact that language contains terms which have multiple meanings. These ambiguities can still be found when language is restricted to a particular domain, such as biomedicine. Word Sense Disambiguation (WSD) systems attempt to resolve these am- biguities but are often only able to identify the meanings for a small set of ambiguous terms. DALE (Disambiguation using Automatically Labeled Examples) is a supervised WSD sys- tem that can disambiguate a wide range of ambiguities found in biomedical documents. DALE uses the UMLS Metathesaurus as both a sense inventory and as a source of infor- mation for automatically generating labeled training examples. DALE is able to disam- biguate biomedical documents with the cover- age of unsupervised ...