Automatic semantic role labeling

HLT-NAACL(2006)

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摘要
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.
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关键词
natural language problem,related task,automatic semantic role,natural language processing community,semantic representation,deep nlp task,existing corpus,question answering,detailed survey,complex information extraction,semantic role,semantic role labeling
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