메뉴 건너뛰기




Volumn , Issue , 2007, Pages 161-164

GYDER: Maxent metonymy resolution

Author keywords

[No Author keywords available]

Indexed keywords

SUBTASKS;

EID: 53049097845     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (12)

References (8)
  • 2
    • 0003973725 scopus 로고
    • English verb classes and alternations
    • The University of Chicago Press
    • Beth Levin. 1993. English Verb Classes and Alternations. A Preliminary Investigation. The University of Chicago Press.
    • (1993) A Preliminary Investigation
    • Levin, B.1
  • 5
    • 70349335909 scopus 로고    scopus 로고
    • Learning to buy a renault and talk to bmw: A supervised approach to conventional metonymy
    • Tilburg, Netherlands
    • Malvina Nissim and Katja Markert. 2005. Learning to buy a Renault and talk to BMW: A supervised approach to conventional metonymy. International Workshop on Computational Semantics (IWCS2005). Tilburg, Netherlands.
    • (2005) International Workshop on Computational Semantics (IWCS2005)
    • Nissim, M.1    Markert, K.2
  • 6
    • 85036455023 scopus 로고    scopus 로고
    • Semeval-2007 task 08: Metonymy resolution at semeval-2007
    • Katja Markert and Malvina Nissim. 2007. SemEval-2007 Task 08: Metonymy Resolution at SemEval-2007. In Proceedings of SemEval-2007.
    • (2007) Proceedings of SemEval-2007
    • Markert, K.1    Nissim, M.2
  • 8
    • 33750685685 scopus 로고    scopus 로고
    • Multilingual named entity recognition system using boosting and c4.5 decision tree learning algorithms
    • Springer- Verlag
    • György Szarvas, Richárd Farkas and András Kocsor. 2006. Multilingual Named Entity Recognition System Using Boosting and C4.5 Decision Tree Learning Algorithms. Proceedings of Discovery Science 2006, DS2006, LNAI 4265 pp. 267-278. Springer-Verlag.
    • (2006) Proceedings of Discovery Science 2006, DS2006, LNAI 4265 , pp. 267-278
    • Szarvas, G.1    Farkas, R.2    Kocsor, A.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.