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Autor*innen: Miller, Tristan; Erbs, Nicolai; Zorn, Hans-Peter; Zesch, Torsten; Gurevych, Iryna
Titel: DKPro WSD - a generalized UIMA-based framework for word sense disambiguation
Aus: Association of Computational Linguistics (Hrsg.): 51st Annual Meeting of the Association for Computational Linguistics: Proceedings of the Conference System Demonstrations, Stroudsburg; PA: Association for Computational Linguistics, 2013 , S. 37-42
URL: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.386.1725&rep=rep1&type=pdf#page=49pdf
Dokumenttyp: 4. Beiträge in Sammelwerken; Tagungsband/Konferenzbeitrag/Proceedings
Sprache: Englisch
Schlagwörter: Ambiguität; Computerlinguistik; Erkennen; Sinn; Software; Wort
Abstract: Implementations of word sense disambiguation (WSD) algorithms tend to be tied to a particular test corpus format and sense inventory. This makes it difficult to test their performance on new data sets, or to compare them against past algorithms implemented for different data sets. In this paper we present DKPro WSD, a freely licensed, general-purpose framework for WSD which is both modular and extensible. DKPro WSD abstracts the WSD process in such a way that test corpora, sense inventories, and algorithms can be freely swapped. Its UIMA-based architecture makes it easy to add support for new resources and algorithms. Related tasks such as word sense induction and entity linking are also supported.
DIPF-Abteilung: Informationszentrum Bildung