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Comparative Study
. 2006 Nov 24;7 Suppl 3(Suppl 3):S2.
doi: 10.1186/1471-2105-7-S3-S2.

Lexical adaptation of link grammar to the biomedical sublanguage: a comparative evaluation of three approaches

Sampo Pyysalo  1 , Tapio Salakoski, Sophie Aubin, Adeline Nazarenko
Affiliations
Comparative Study

Lexical adaptation of link grammar to the biomedical sublanguage: a comparative evaluation of three approaches

Sampo Pyysalo et al. BMC Bioinformatics. .

Abstract

Background: We 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.

Results: 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 significant 10% relative decrease in error.

Conclusion: When available, a high-quality domain part-of-speech tagger is the best solution to unknown word issues in the domain adaptation of a general parser. In the absence of such a resource, surface clues can provide remarkably good coverage and performance when tuned to the domain. The adapted parser is available under an open-source license.

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Figures

Figure 1
Figure 1
Example Link Grammar Parser linkages.
Figure 2
Figure 2
Vocabulary handling in the interaction and transcript corpora.
See this image and copyright information in PMC

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