REES: a large-scale relation and event extraction system

Authors:
Chinatsu Aone;Mila Ramos-Santacruz
Affiliations:
SRA International, Inc., Fairfax, VA;SPA International, Inc., Fairfax, VA
Venue:
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
Year:
2000

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Abstract

This paper reports on a large-scale, end-to-end relation and event extraction system. At present, the system extracts a total of 100 types of relations and events, which represents a much wider coverage than is typical of extraction systems. The system consists of three specialized pattern-based tagging modules, a high-precision coreference resolution module, and a configurable template generation module. We report quantitative evaluation results, analyze the results in detail, and discuss future directions.