DocumentCode :
2595179
Title :
Semantic parsing as an energy minimization problem
Author :
Chan, Samuel W K
Author_Institution :
Dept. of Comput. Sci., City Univ. of Hong Kong, China
Volume :
2
fYear :
1997
fDate :
28-31 Oct 1997
Firstpage :
1118
Abstract :
Language understanding is not just a matter of knowing the language but, to a considerable degree, it is a matter of logical inference using world knowledge. A pure linguistic approach cannot interpret any natural language utterances; it can only constrain their interpretation, and the rest must be left to semantic parsing. To discriminate sense in any semantic parsing, a reader should consider a diversity of information, including syntactic tags and restriction, word frequencies, collocations, semantic context and role-related expectations. However, current approaches make use of only small subsets of this information. In this paper, we show how semantic parsing can be formulated as a sequence of processes in which multiple sources of knowledge are incorporated. A resolution-based inference procedure is shown to determine semantic meanings from the analyzed utterances. This is done on the basis that language technology has to employ test-efficient solutions with respect to the phenomena occurring in real-world language understanding
Keywords :
flowcharting; grammars; inference mechanisms; minimisation; natural languages; collocations; energy minimization; language technology; language understanding; linguistic approach; logical inference; meaning discrimination; multiple knowledge sources; natural language utterance interpretation; resolution-based inference procedure; role-related expectations; semantic context; semantic parsing; syntactic restriction; syntactic tags; test-efficient solutions; word frequencies; world knowledge; Computer science; Context modeling; Dictionaries; Encoding; Energy resolution; Frequency diversity; Natural languages; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Processing Systems, 1997. ICIPS '97. 1997 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
0-7803-4253-4
Type :
conf
DOI :
10.1109/ICIPS.1997.669157
Filename :
669157
Link To Document :
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