Semantic Lexicon Population Task
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A Semantic Lexicon Population Task is a dictionary population task whose database is a semantic lexicon.
- Context:
- It can be performed by a Semantic Lexicon Population System (that implements a Semantic Lexicon Population algorithm).
- See: Dictionary Population Task.
References
2012
- (Qadir & Riloff, 2012) ⇒ Ashequl Qadir, and Ellen Riloff. (2012). “Ensemble-based Semantic Lexicon Induction for Semantic Tagging.” In: Proceedings of the First Joint Conference on Lexical and Computational Semantics (*Sem 2012).
- QUOTE: One of the most fundamental aspects of meaning is the association between words and semantic categories, which allows us to understand that a “cow” is an animal and a “house” is a structure. We will use the term semantic lexicon to refer to a dictionary that associates words with semantic classes. Semantic dictionaries are useful for many NLP tasks, as evidenced by the widespread use of WordNet (Miller, 1990). However, off-the-shelf resources are not always sufficient for specialized domains, such as medicine, chemistry, or microelectronics. Furthermore, in virtually every domain, texts contain lexical variations that are often missing from dictionaries, such as acronyms, abbreviations, spelling variants, informal shorthand terms (e.g., “abx” for “antibiotics”), and composite terms (e.g., “may-december” or “virus/worm”). To address this problem, techniques have been developed to automate the construction of semantic lexicons from text corpora using bootstrapping methods (Riloff and Shepherd, 1997; Roark and Charniak, 1998; Phillips and Riloff, 2002; Thelen and Riloff, 2002; Ng, 2007; McIntosh and Curran, 2009; McIntosh, 2010), but accuracy is still far from perfect.