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Expert-built and collaboratively constructed lexical semantic resources
Abstract Knowledge about words, their meanings, andKnowledge about words, their meanings, and their relations to other words contained in lexical semantic resources is of particular interest for the automatic processing of human language. In the last decades, expert-built lexical semantic resources such as WordNet have been utilized in a vast number of natural language processing (NLP) tasks. Recently, collaboratively constructed resources such as the online encyclopedia Wikipedia with its exceptional scale and Wiktionary, a combination of dictionary and thesaurus, have been discovered as valuable substitutes for expert-built resources. In this study, we first introduce diverse types of lexical semantic resources with respect to their content and structure. We identify the differences between expert-built and collaboratively constructed resources and compare WordNet, Wiktionary, and Wikipedia. We provide a comprehensive overview of the lexical semantic knowledge therein and discuss their assets and drawbacks. Finally, we review work on orchestrating different resources in order to combine their strengths and explore their use in major NLP applications.plore their use in major NLP applications.
Added by wikilit team Added on initial load  +
Collected data time dimension Cross-sectional  +
Comments It turned out that both Wiktionary and Wikipedia are emerging resources for various NLP tasks as they perform competitively to expert-built LSRs when used as a source of lexical semantic knowledge.
Conclusion In this study, we introduced diverse typesIn this study, we introduced diverse types of LSRs and identified and discussed the major differences between expert-built and collaboratively constructed LSRs. For comparison, we chose WordNet, an instance of an expert-built LSR, and Wiktionary as its collaboratively constructed correspondent. Furthermore, we analyzed Wikipedia and provided a comprehensive overview of the encoded lexical semantic knowledge therein. It turned out that both Wiktionary and Wikipedia are emerging resources for various NLP tasks as they perform competitively to expert-built LSRs when used as a source of lexical semantic knowledge. We reviewed some recent works, which aim at aligning ELSRs and CLSRs and briefly described major NLP tasks in which these resources are utilized.sks in which these resources are utilized.
Data source Websites  +
Doi 10.1111/j.1749-818X.2010.00251.x +
Google scholar url http://scholar.google.com/scholar?ie=UTF-8&q=%22Expert-built%2Band%2Bcollaboratively%2Bconstructed%2Blexical%2Bsemantic%2Bresources%22  +
Has author Iryna Gurevych + , Elisabeth Wolf +
Has domain Computer science +
Has topic Computational linguistics +
Issue 11  +
Pages 1074-1090  +
Peer reviewed Yes  +
Publication type Journal article  +
Published in Language and Linguistics Compass +
Research design Case study  +
Research questions In this study, we introduce different typeIn this study, we introduce different types of lexical semantic resources (LSRs) that capture lexical semantic information about the content and structure of words. We distinguish between conventional LSRs and resources created collaboratively by ordinary web users. We discuss and compare some of the major resources, i.e. WordNet, Wiktionary, and Wikipedia, with respect to the lexical semantic knowledge therein, and analyze their assets and drawbacks. Finally, we review work on orchestrating different resources in order to combine their strengths and examine the use of LSRs in core NLP applications. the use of LSRs in core NLP applications.
Revid 10,757  +
Theories Undetermined
Theory type Analysis  +
Title Expert-built and collaboratively constructed lexical semantic resources
Unit of analysis Website  +
Url http://doi.wiley.com/10.1111/j.1749-818X.2010.00251.x  +
Volume 4  +
Wikipedia coverage Case  +
Wikipedia data extraction Live Wikipedia  +
Wikipedia language English  +
Wikipedia page type Article  + , Information categorization and navigation  +
Year 2010  +
Creation dateThis property is a special property in this wiki. 15 March 2012 20:26:33  +
Categories Computational linguistics  + , Computer science  + , Publications  +
Modification dateThis property is a special property in this wiki. 30 January 2014 20:26:10  +
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