Categorising Modality in Biomedical Texts (Contributo in atti di convegno)

Type

• Prodotto della ricerca (Classe)
• Contributo in atti di convegno (Classe)

Label

• Categorising Modality in Biomedical Texts (Contributo in atti di convegno) (literal)

Anno

• 2008-01-01T00:00:00+01:00 (literal)

Alternative label

• Thompson P.; Venturi G.; McNaught J.; Montemagni S.; Ananiadou S. (2008)
  Categorising Modality in Biomedical Texts
  in LREC 2008, Sixth International Conference on Language Resources and Evaluation: Workshop 'Building and Evaluating Resources for Biomedical Text Mining', Marrakech, Marocco, 26 maggio 2008
  (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori

• Thompson P.; Venturi G.; McNaught J.; Montemagni S.; Ananiadou S. (literal)

Pagina inizio

• 27 (literal)

Pagina fine

• 34 (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#note

• In: LREC - LREC 2008, Sixth International Conference on Language Resources and Evaluation: Workshop 'Building and Evaluating Resources for Biomedical Text Mining' (Palais des Congrès Mansour Eddahbi, Marrakech, Maroc, 26 May - 1 June 2008). Proceedings, pp. 27 - 34. Nicoletta Calzolari (Conference Chair), Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odjik, Stelios Piperidis, Daniel Tapias (eds.). European Language Resources Association (ELRA), 2008. (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#descrizioneSinteticaDelProdotto

• ABSTRACT: The accurate recognition of modal information is vital for the correct interpretation of statements. In this paper, we report on the collection a list of words and phrases that express modal information in biomedical texts, and propose a categorisation scheme according to the type of information conveyed. We have performed a small pilot study through the annotation of 202 MEDLINE abstracts according to our proposed scheme. Our initial results suggest that modality in biomedical statements can be predicted fairly reliably though the presence of particular lexical items, together with a small amount of contextual information. (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni

• Thompson Paul, McNaught John, Ananiadou Sophia: University of Manchester, UK. Venturi G., Montemagni S.: ILC - Istituto di linguistica computazionale \"Antonio Zampolli\" (literal)

Titolo

• Categorising Modality in Biomedical Texts (literal)

Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn

• 2-9517408-4-0 (literal)

Abstract

• The accurate recognition of modal information is vital for the correct interpretation of statements. In this paper, we report on the collection a list of words and phrases that express modal information in biomedical texts, and propose a categorisation scheme according to the type of information conveyed. We have performed a small pilot study through the annotation of 202 MEDLINE abstracts according to our proposed scheme. Our initial results suggest that modality in biomedical statements can be predicted fairly reliably though the presence of particular lexical items, together with a small amount of contextual information. (literal)

Prodotto di

• Tecnologie linguistiche e gestione della conoscenza (IC.P02.004.001) (Modulo)
• Institute of computational linguistics \"Antonio Zampolli\" (ILC) (Istituto)

Autore CNR

• SIMONETTA MONTEMAGNI (Unità di personale interno)
• GIULIA VENTURI (Persona)

Insieme di parole chiave

• Parole chiave di "Categorising Modality in Biomedical Texts" (Insieme di parole chiave)

Incoming links:

Autore CNR di

• SIMONETTA MONTEMAGNI (Unità di personale interno)
• GIULIA VENTURI (Persona)

Prodotto

• Institute of computational linguistics \"Antonio Zampolli\" (ILC) (Istituto)
• Tecnologie linguistiche e gestione della conoscenza (IC.P02.004.001) (Modulo)

Insieme di parole chiave di

• Parole chiave di "Categorising Modality in Biomedical Texts" (Insieme di parole chiave)