Lexical Adaptation of Link Grammar to the Biomedical Sublanguage: a Comparative Evaluation of Three Approaches

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dc.creatorPyysalo, Sampo
dc.creatorSalakoski, Tapio
dc.creatorAubin, Sophie
dc.creatorNazarenko, Adeline
dc.date2006-06-28
dc.date.accessioned2026-07-07T07:13:07Z
dc.date.available2026-07-07T07:13:07Z
dc.descriptionWe study the adaptation of Link Grammar Parser to the biomedical sublanguage with a focus on domain terms not found in a general parser lexicon. Using two biomedical corpora, we implement and evaluate three approaches to addressing unknown words: automatic lexicon expansion, the use of morphological clues, and disambiguation using a part-of-speech tagger. We evaluate each approach separately for its effect on parsing performance and consider combinations of these approaches. In addition to a 45% increase in parsing efficiency, we find that the best approach, incorporating information from a domain part-of-speech tagger, offers a statistically signicant 10% relative decrease in error. The adapted parser is available under an open-source license at http://www.it.utu.fi/biolg.
dc.identifierhttps://arxiv.org/abs/cs/0606119
dc.identifierhttp://arxiv.org/abs/cs/0606119
dc.identifierProceedings of the Second International Symposium on Semantic Mining in Biomedicine (SMBM 2006) (2006) 60-67
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/112333
dc.subjectComputation and Language
dc.subjectInformation Retrieval
dc.subjectH.4
dc.titleLexical Adaptation of Link Grammar to the Biomedical Sublanguage: a Comparative Evaluation of Three Approaches
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