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Identifying senses of particles in verb-particle constructions

Archna Bhatia; Choh Man Teng; James F. Allen

In order to attain broad coverage understanding, a system need not only identify
multiword expressions such as verb-particle constructions (VPCs), but must compute their meaning. It is not plausible to hand enumerate all possible combinations,
although WordNet is an admirable start. This chapter focuses on the identification
of senses of particles in VPCs in order to compute the meanings of VPCs – using
information obtained from existing lexical resources such as WordNet, and aug-
menting it with additional knowledge based on linguistic investigation of VPCs
identified in terms of generalizations encoded in the TRIPS ontology. The approach
consists of first determining compositionality of a VPC based on the information
present in WordNet, and then assigning a relevant sense to the particle in a compositional VPC based on the sense classes we have identified and encoded in the
TRIPS’ computational lexicon. Contributions of the described work are twofold:
(1) A discussion of senses of particles in VPCs and corresponding generalizations
makes a linguistic contribution. (2) We show how linguistic knowledge can be used
to automatically parse sentences containing VPCs and obtain a semantic representation of them. An advantage of the described approach is that VPCs not explicitly
found in lexica can be identified and semantically interpreted.


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