Domain portability and adaptation of NLP components and Word Sense Disambiguation systems present new challenges. The difficulties found by supervised systems to adapt might change the way we assess the strengths and weaknesses of supervised and knowledgebased WSD systems. Unfortunately, all existing evaluation datasets for specific domains are lexical-sample corpora. With this paper we want to motivate the creation of an allwords test dataset for WSD on the environment domain in several languages, and present the overall design of this SemEval task.
SemEval-2010 Task 17: All-words Word Sense Disambiguation on a Specific Domain
Marchetti Andrea;
2009
Abstract
Domain portability and adaptation of NLP components and Word Sense Disambiguation systems present new challenges. The difficulties found by supervised systems to adapt might change the way we assess the strengths and weaknesses of supervised and knowledgebased WSD systems. Unfortunately, all existing evaluation datasets for specific domains are lexical-sample corpora. With this paper we want to motivate the creation of an allwords test dataset for WSD on the environment domain in several languages, and present the overall design of this SemEval task.File in questo prodotto:
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