Computational Models of Language Within Context and Context-Sensitive Language Understanding
Noriko Ito*, Toru Sugimoto**, Yusuke Takahashi***,
Shino Iwashita****, and Michio Sugeno*
*Doshisha University, 1-3 Tatara Miyakodani, Kyotanabe, Kyoto 610-0394, Japan
**Brain Science Institute, RIKEN, 2-1 Hirosawa, Wako, Saitama 351-0198, Japan
***Justsystem Corporation, Aoyama bldg. 1-2-3 Kita-Aoyama, Minato-ku, Tokyo 107-8640, Japan
****Kyushu University, 4-9-1 Shiobaru, Minami-ku, Fukuoka 815-8540, Japan
We propose two computational models – one of a language within context based on systemic functional linguistic theory and one of context-sensitive language understanding. The model of a language within context called the Semiotic Base characterizes contextual, semantic, lexicogrammatical, and graphological aspects of input texts. The understanding process is divided into shallow and deep analyses. Shallow analysis consists of morphological and dependency analyses and word concept and case relation assignment, mainly by existing natural language processing tools and machine-readable dictionaries. Results are used to detect the contextual configuration of input text in contextual analysis. This is followed by deep analyses of lexicogrammar, semantics, and concepts, conducted by referencing a subset of resources related to the detected context. Our proposed models have been implemented in Java and verified by integrating them into such applications as dialog-based question-and-answer (Q&A).
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