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.
Keywords
- Machine Translation
- Power Grid
- Semantic Network
- Semantic Role
- Source Text
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© 2002 Springer-Verlag Berlin Heidelberg
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Nyberg, E., Mitamura, T., Baker, K., Svoboda, D., Peterson, B., Williams, J. (2002). Deriving Semantic Knowledge from Descriptive Texts Using an MT System. In: Richardson, S.D. (eds) Machine Translation: From Research to Real Users. AMTA 2002. Lecture Notes in Computer Science(), vol 2499. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45820-4_15
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DOI: https://doi.org/10.1007/3-540-45820-4_15
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