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Classic monolingual Word Sense Disambiguation evaluation tasks uses WordNet as its sense inventory and is largely based on supervised / semi-supervised classification with the manually sense annotated corpora:〔Lucia Specia, Maria das Gracas Volpe Nunes, Gabriela Castelo Branco Ribeiro, and Mark Stevenson. ( Multilingual versus monolingual WSD ). In EACL-2006 Workshop on Making Sense of Sense: Bringing Psycholinguistics and Computational Linguistics Together, pages 33–40, Trento, Italy, April 2006.〕 *Classic English WSD uses the Princeton WordNet as it sense inventory and the primary classification input is normally based on the ( SemCor ) corpus. *Classical WSD for other languages uses their respective WordNet as sense inventories and sense annotated corpora tagged in their respective languages. Often researchers will also tapped on the SemCor corpus and aligned bitexts with English as its source language == Sense inventories == During the first Senseval workshop the HECTOR sense inventory was adopted. The reason for adopting a previously unknown sense inventory was mainly to avoid the use of popular fine-grained word senses (such as WordNet), which could make the experiments unfair or biased. However, given the lack of coverage of such inventories, since the second Senseval workshop the WordNet sense inventory has been adopted. WSD exercises require a dictionary, to specify the word senses which are to be disambiguated, and a corpus of language data to be disambiguated. WordNet is the most popular example of sense inventory. The reason for adopting the HECTOR database during Senseval-1 was that the WordNet inventory was already publicly available.〔Adam Kilgarriff and Joseph Rosenzweig. 2000. ( English Framework and Results ). Computers and the Humanities 34 (1-2), Special Issue on SENSEVAL.〕 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Classic monolingual word-sense disambiguation」の詳細全文を読む スポンサード リンク
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