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Автор GROVER, CLAIRE
Автор LASCARIDES, ALEX
Автор LAPATA, MIRELLA
Дата выпуска 2005
dc.description This paper reports on a number of experiments which are designed to investigate the extent to which current NLP resources are able to syntactically and semantically analyse biomedical text. We address two tasks: (a) parsing a real corpus with a hand-built wide-coverage grammar, producing both syntactic analyses and logical forms and (b) automatically computing the interpretation of compound nouns where the head is a nominalisation (e.g. hospital arrival means an arrival at hospital, while patient arrival means an arrival of a patient). For the former task we demonstrate that flexible and yet constrained pre-processing techniques are crucial to success: these enable us to use part-of-speech tags to overcome inadequate lexical coverage, and to package up complex technical expressions prior to parsing so that they are blocked from creating misleading amounts of syntactic complexity. We argue that the XML-processing paradigm is ideally suited for automatically preparing the corpus for parsing. For the latter task, we compute interpretations of the compounds by exploiting surface cues and meaning paraphrases, which in turn are extracted from the parsed corpus. This provides an empirical setting in which we can compare the utility of a comparatively deep parser vs. a shallow one, exploring the trade-off between resolving attachment ambiguities on the one hand and generating errors in the parses on the other. We demonstrate that a model of the meaning of compound nominalisations is achievable with the aid of current broad-coverage parsers.
Издатель Cambridge University Press
Название A comparison of parsing technologies for the biomedical domain
DOI 10.1017/S1351324904003547
Electronic ISSN 1469-8110
Print ISSN 1351-3249
Журнал Natural Language Engineering
Том 11
Первая страница 27
Последняя страница 65
Аффилиация GROVER CLAIRE; The University of Edinburgh
Аффилиация LASCARIDES ALEX; The University of Edinburgh
Аффилиация LAPATA MIRELLA; University of Sheffield
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