Elaborating a knowledge base for deep lexical semantics

Authors:
Niloofar Montazeri;Jerry R. Hobbs
Affiliations:
University of Southern California, Marina del Rey, California;University of Southern California, Marina del Rey, California
Venue:
IWCS '11 Proceedings of the Ninth International Conference on Computational Semantics
Year:
2011

Citing 7
Cited 1

Interpretation as abduction

Artificial Intelligence - Special volume on natural language processing
The process specification language (PSL) theory and applications

AI Magazine
Ontological promiscuity

ACL '85 Proceedings of the 23rd annual meeting on Association for Computational Linguistics
Commonsense Reasoning

Commonsense Reasoning
Deep lexical semantics

CICLing'08 Proceedings of the 9th international conference on Computational linguistics and intelligent text processing
Implementing weighted abduction in Markov logic

IWCS '11 Proceedings of the Ninth International Conference on Computational Semantics
Abductive reasoning with a large knowledge base for discourse processing

IWCS '11 Proceedings of the Ninth International Conference on Computational Semantics

Influences and inferences

Computational Linguistics

Quantified Score

Hi-index	0.00

Visualization

Abstract

We describe the methodology for constructing axioms defining event-related words, anchored in core theories of change of state and causality. We first derive from WordNet senses a smaller set of abstract, general "supersenses". We encode axioms for these, and we test them on textual entailment pairs. We look at two specific examples in detail to illustrate both the power of the method and the holes in the knowledge base that it exposes. Then we address the problem of holes more systematically, asking, for example, what kinds of "pairwise interactions" are possible for core theory predicates like change and cause.