Deriving semantic knowledge from descriptive texts using an MT system

Eric Nyberg, Teruko Mitamura, Kathryn Baker, David Svoboda, Brian Peterson, Jennifer Williams


Abstract
This paper describes the results of a feasibility study which focused on deriving semantic networks from descriptive texts using controlled language. The KANT system [3,6] was used to analyze input paragraphs, producing sentence-level interlingua representations. The interlinguas were merged to construct a paragraph-level representation, which was used to create a semantic network in Conceptual Graph (CG) [1] format. The interlinguas are also translated (using the KANTOO generator) into OWL statements for entry into the Ontology Works electrical power factbase [9]. The system was extended to allow simple querying in natural language.
Anthology ID:
2002.amta-papers.15
Volume:
Proceedings of the 5th Conference of the Association for Machine Translation in the Americas: Technical Papers
Month:
October 8-12
Year:
2002
Address:
Tiburon, USA
Venue:
AMTA
SIG:
Publisher:
Springer
Note:
Pages:
145–154
Language:
URL:
https://link.springer.com/chapter/10.1007/3-540-45820-4_15
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PDF:
https://link.springer.com/chapter/10.1007/3-540-45820-4_15