The Acquisition of Common Sense Knowledge by Being Told: An Application of NLP to Itself

Authors:
Fernando Gomez
Affiliations:
School of EECS, University of Central Florida, Orlando FL 32816
Venue:
NLDB '08 Proceedings of the 13th international conference on Natural Language and Information Systems: Applications of Natural Language to Information Systems
Year:
2008

Citing 7
Cited 0

Automatic sense disambiguation using machine readable dictionaries: how to tell a pine cone from an ice cream cone

SIGDOC '86 Proceedings of the 5th annual international conference on Systems documentation
An integrated, dual learner for grammars and ontologies

Data & Knowledge Engineering
ConceptNet — A Practical Commonsense Reasoning Tool-Kit

BT Technology Journal
A method for word sense disambiguation of unrestricted text

ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Logic form transformation of WordNet and its applicability to question answering

ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
An algorithm for aspects of semantic interpretation using an enhanced WordNet

NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
Building verb predicates: a computational view

ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper shows how the knowledge of a semantic interpreter can be bootstrapped for other semantic interpretation tasks. Methods are described for automatically acquiring common sense knowledge and for applying this knowledge to noun sense disambiguation. Ordinary concepts are described by several plain English sentences that are parsed and semantically interpreted. The semantic interpreted sentences are stored under these concepts to be used for semantic interpretation tasks. This paper explains the description of the concepts, the interpretation of the sentences and two algorithms for noun sense disambiguation that use the acquired knowledge.