Automatic semantic role labeling. Yih, S., W. & Toutanova, K. In Proceedings of the Human Language Technology Conference of the NAACL Companion Volume Tutorial Abstracts on XX, pages 309–310, 2006. Association for Computational Linguistics.
Automatic semantic role labeling [link]Website  abstract   bibtex   
The goal of semantic role labeling is to map sentences to domain-independent semantic representations, which abstract away from syntactic structure and are important for deep NLP tasks such as question answering, textual entailment, and complex information extraction. Semantic role labeling has recently received significant interest in the natural language processing community. In this tutorial, we will first describe the problem and history of semantic role labeling, and introduce existing corpora and other related tasks. Next, we will provide a detailed survey of state-of-the-art machine learning approaches to building a semantic role labeling system. Finally, we will conclude the tutorial by discussing directions for improving semantic role labeling systems and their application to other natural language problems.
@inProceedings{
 title = {Automatic semantic role labeling},
 type = {inProceedings},
 year = {2006},
 pages = {309–310},
 websites = {http://portal.acm.org/citation.cfm?id=1614107},
 publisher = {Association for Computational Linguistics},
 id = {8ef21c9e-36a8-39b1-953c-72d9bc2b03f9},
 created = {2012-02-28T00:51:15.000Z},
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 last_modified = {2017-03-14T14:36:19.698Z},
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 abstract = {The goal of semantic role labeling is to map sentences to domain-independent semantic representations, which abstract away from syntactic structure and are important for deep NLP tasks such as question answering, textual entailment, and complex information extraction. Semantic role labeling has recently received significant interest in the natural language processing community. In this tutorial, we will first describe the problem and history of semantic role labeling, and introduce existing corpora and other related tasks. Next, we will provide a detailed survey of state-of-the-art machine learning approaches to building a semantic role labeling system. Finally, we will conclude the tutorial by discussing directions for improving semantic role labeling systems and their application to other natural language problems.},
 bibtype = {inProceedings},
 author = {Yih, S W and Toutanova, K},
 booktitle = {Proceedings of the Human Language Technology Conference of the NAACL Companion Volume Tutorial Abstracts on XX}
}
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