TY - CHAP
T1 - A systemic-functional approach to Japanese text understanding
AU - Ito, Noriko
AU - Sugimoto, Toru
AU - Sugeno, Michio
PY - 2004
Y1 - 2004
N2 - We have implemented a Japanese text processing system, combining the existing parser and dictionary with the linguistic resources that we developed based on systemic functional linguistics. In this paper, we explain the text understanding algorithm of our system that utilizes the various linguistic resources in the Semiotic Base suggested by Halliday. First, we describe the structure of the SB and the linguistic resources stored in it. Then, we depict the text understanding algorithm using the SB. The process starts with morphological and dependency analyses by the non-SFL-based existing parser, followed by looking up the dictionary to enrich the input for SFL-based analysis. After mapping the pre-processing results onto systemic features, the path identification of selected features and unification based on O'Donnell are conducted with reference to the linguistic resource represented in the system networks. Consequently, we obtain graphological, lexicogrammatical, semantic and conceptual annotations of a given text.
AB - We have implemented a Japanese text processing system, combining the existing parser and dictionary with the linguistic resources that we developed based on systemic functional linguistics. In this paper, we explain the text understanding algorithm of our system that utilizes the various linguistic resources in the Semiotic Base suggested by Halliday. First, we describe the structure of the SB and the linguistic resources stored in it. Then, we depict the text understanding algorithm using the SB. The process starts with morphological and dependency analyses by the non-SFL-based existing parser, followed by looking up the dictionary to enrich the input for SFL-based analysis. After mapping the pre-processing results onto systemic features, the path identification of selected features and unification based on O'Donnell are conducted with reference to the linguistic resource represented in the system networks. Consequently, we obtain graphological, lexicogrammatical, semantic and conceptual annotations of a given text.
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U2 - 10.1007/978-3-540-24630-5_3
DO - 10.1007/978-3-540-24630-5_3
M3 - Chapter
AN - SCOPUS:35048904613
SN - 3540210067
SN - 9783540210061
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 26
EP - 37
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
A2 - Gelbukh, Alexander
PB - Springer Verlag
ER -