http://www.cnr.it/ontology/cnr/individuo/prodotto/ID112956
Bootstrapping a Verb Lexicon for Biomedical Information Extraction (Comunicazione a convegno)
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- Bootstrapping a Verb Lexicon for Biomedical Information Extraction (Comunicazione a convegno) (literal)
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- 2009-01-01T00:00:00+01:00 (literal)
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Venturi, Giulia; Montemagni, Simonetta; Marchi, Simone; Sasaki, Yutaka; Thompson, Paul; McNaught, John; Ananiadou, Sophia (2009)
Bootstrapping a Verb Lexicon for Biomedical Information Extraction
in International Conference on Intelligent Text Processing and Computational Linguistics (CICLing 2009), Mexico City, Mexico, March 1-7, 2009
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- Venturi, Giulia; Montemagni, Simonetta; Marchi, Simone; Sasaki, Yutaka; Thompson, Paul; McNaught, John; Ananiadou, Sophia (literal)
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- Proceedings of the 10th International Conference on Intelligent Text Processing and Computational Linguistics (CICLing 2009) (literal)
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- In: SLI-2010 - XLIV Congresso Internazionale di Studi della Società di Linguistica Italiana (Viterbo, Università degli Studi della Tuscia, 27-29 settembre 2010). (literal)
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- The presentation will illustrate whether and how linguistic technologies can be used to monitor the language learning process. (literal)
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- Titolo
- Bootstrapping a Verb Lexicon for Biomedical Information Extraction (literal)
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- 978-3-642-00381-3 (literal)
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- Alexander Gelbukh (literal)
- Abstract
- The extraction of information from texts requires resources that contain both syntactic and semantic properties of lexical units. As the use Of language in specialized domains, such as biology, can be very different to the general domain, there is a need for domain-specific resources to ensure that the information extracted is as accurate as possible. We are building a large-scale lexical resource for the biology domain. providing information about predicate-argument structure that has been bootstrapped from a biomedical corpus on the subject of E. Coli. The lexicon is currently focussed on verbs, and includes both automatically-extracted syntactic subcategorization frames, as well as semantic event frames that are based on annotation by domain experts. In addition, the lexicon contains manually-added explicit links between semantic and syntactic slots in corresponding frames. To Our knowledge, this lexicon currently represents a unique resource within in the biomedical domain. (literal)
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