Abstract
Verbs play an important role in the understanding of natural language text. This paper studies the problem of abstracting the subject and object arguments of a verb into a set of noun concepts, known as the "argument concepts". This set of concepts, whose size is parameterized, represents the finegrained semantics of a verb. For example, the object of "enjoy" can be abstracted into time, hobby and event, etc. We present a novel framework to automatically infer human readable and machine computable action concepts with high accuracy.
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CITATION STYLE
Gong, Y., Zhao, K., & Zhu, K. Q. (2016). Representing verbs as argument concepts. In 30th AAAI Conference on Artificial Intelligence, AAAI 2016 (pp. 2615–2621). AAAI press. https://doi.org/10.1609/aaai.v30i1.10324
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