Work

VerbNet Representations: Subevent Semantics for Transfer Verbs

Year: 2019

Type: conference-paper

Abstract: This paper announces the release of a new version of the English lexical resource VerbNet with substantially revised semantic representations designed to facilitate computer planning and reasoning based on human language.We use the transfer of possession and transfer of information event representations to illustrate both the general framework of the representations and the types of nuances the new representations can capture.These representations use a Generative Lexicon-inspired subevent structure to track attributes of event participants across time, highlighting oppositions and temporal and causal relations among the subevents.

DOI: 10.18653/v1/w19-3318

Authors: Susan Windisch Brown, Julia Bonn, James Gung, Annie Zaenen, James Pustejovsky, Martha Palmer

Institutions: Stanford University, Brandeis University

Language: English

Topic: Natural Language Processing Techniques

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Funders: Defense Advanced Research Projects Agency, Defense Threat Reduction Agency, University of Illinois at Urbana-Champaign

Award: G2680891558

OpenAlex ID: W2972809615