DocumentCode :
2118034
Title :
Deep domain models for discourse analysis
Author :
Joskowicz, Leo ; Ksiezyck, T. ; Grishman, Ralph
Author_Institution :
Dept. of Comput. Sci., New York Univ., NY, USA
fYear :
1989
fDate :
27-31 Mar 1989
Firstpage :
195
Lastpage :
200
Abstract :
The authors address the problem of discourse analysis, and in particular finding causal relations between facts mentioned in messages, using a detailed domain model. This work is part of the PROTEUS (Prototype Text Understanding System) project, whose objective is to understand short narrative message about equipment installed in Navy ships. Casualty reports (CASREPs) describe failures of this equipment, together with maintenance actions performed by the crew onboard. To capture the domain knowledge, the authors built a model of the equipment installed on the ship (initially, the starting air system) and demonstrated is use in several aspects of language understanding. The PROTEUS system has been substantially implemented and debugged and has been publically demonstrated operating on a small set of actual CASREPs
Keywords :
knowledge acquisition; maintenance engineering; natural languages; naval engineering; CASREPs; Navy ships; PROTEUS; Prototype Text Understanding System; casualty reports; causal relations; discourse analysis; domain knowledge; language understanding; maintenance actions; narrative message; starting air system; Computational modeling; Computer science; Computer simulation; Equipment failure; Marine vehicles; Mathematical model; Natural language processing; Natural languages; Prototypes; Robustness;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
AI Systems in Government Conference, 1989.,Proceedings of the Annual
Conference_Location :
Washington, DC
Print_ISBN :
0-8186-1934-1
Type :
conf
DOI :
10.1109/AISIG.1989.47325
Filename :
47325
Link To Document :
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