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VerbNet

The VerbNet project maps PropBank verb types to their corresponding Levin classes. It is a lexical resource that incorporates both semantic and… Expand
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Papers overview

Semantic Scholar uses AI to extract papers important to this topic.
2017
2017
Massive digital datasets, such as social media data, are a promising source to study social and cultural phenomena. They provide… Expand
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Highly Cited
2010
Highly Cited
2010
Extracting temporal information from raw text is fundamental for deep language understanding, and key to many applications like… Expand
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Highly Cited
2006
Highly Cited
2006
Lexical classifications have proved useful in supporting various natural language processing (NLP) tasks. The largest verb… Expand
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2006
2006
Lexical classifications have proved useful in supporting various linguistic and natural language processing (NLP) tasks. The… Expand
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Highly Cited
2006
Highly Cited
2006
A wide variety of lexical resources have been created to allow automatic semantic processing of novel text. However, each… Expand
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Highly Cited
2005
Highly Cited
2005
Despite the proliferation of approaches to lexicon development, the field of natural language processing has yet to develop a… Expand
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Highly Cited
2005
Highly Cited
2005
This paper describes our work in integrating three different lexical resources: FrameNet, VerbNet, and WordNet, into a unified… Expand
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2005
2005
There is disclosed a multi-purpose golfer's tool. The tool provides a distance estimating facility which in turn provides… Expand
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2004
2004
In this paper, we present a high accurate system for FrameNet semantic role classification based on the innovative features… Expand
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2003
2003
A ball bat is provided and comprises a body member which terminates a tone end with a hollow handle portion having a pair of… Expand
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