Keywords

information extraction, machine reading, cognitive agent

Abstract

Machine reading is a relatively new field that features computer programs designed to read flowing text and extract fact assertions expressed by the narrative content. This task involves two core technologies: natural language processing (NLP) and information extraction (IE). In this paper we describe a machine reading system that we have developed within a cognitive architecture. We show how we have integrated into the framework several levels of knowledge for a particular domain, ideas from cognitive semantics and construction grammar, plus tools from prior NLP and IE research. The result is a system that is capable of reading and interpreting complex and fairly idiosyncratic texts in the family history domain. We describe the architecture and performance of the system. After presenting the results from several evaluations that we have carried out, we summarize possible future directions.

Original Publication Citation

Peter Lindes, Deryle Lonsdale, and David Embley (2015). Ontology-based Information Extraction with a Cognitive Agent. Proceedings of the Twenty-Ninth Conference on ArtificialIntelligence by the Association for the Advancement of Artificial Intelligence (AAAI 2015), pp.558-564; AAAI Press, Palo Alto, CA; ISBN 978-1-57735-698-1.

Document Type

Conference Paper

Publication Date

2015

Publisher

Association for the Advancement of Artificial Intelligence

Language

English

College

Humanities

Department

Linguistics

University Standing at Time of Publication

Associate Professor

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Linguistics Commons

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