Three-Phase English Syntactic Analysis for Improving the Parsing Efficiency


KIPS Transactions on Software and Data Engineering, Vol. 5, No. 1, pp. 21-28, Jan. 2016
10.3745/KTSDE.2016.5.1.21,   PDF Download:

Abstract

The performance of an English-Korean machine translation system depends heavily on its English parser. The parser in this paper is a part of the rule-based English-Korean MT system, which includes many syntactic rules and performs the chart-based parsing. The parser generates too many structures due to many syntactic rules, so much time and memory are required. The rule-based parser has difficulty in analyzing and translating the long sentences including the commas because they cause high parsing complexity. In this paper, we propose the 3-phase parsing method with sentence segmentation to efficiently translate the long sentences appearing in usual. Each phase of the syntactic analysis applies its own independent syntactic rules in order to reduce parsing complexity. For the purpose, we classify the syntactic rules into 3 classes and design the 3-phase parsing algorithm. Especially, the syntactic rules in the 3rd class are for the sentence structures composed with commas. We present the automatic rule acquisition method for 3rd class rules from the syntactic analysis of the corpus, with which we aim to continuously improve the coverage of the parsing. The experimental results shows that the proposed 3-phase parsing method is superior to the prior parsing method using only intra-sentence segmentation in terms of the parsing speed/memory efficiency with keeping the translation quality.


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Cite this article
[IEEE Style]
S. D. Kim, "Three-Phase English Syntactic Analysis for Improving the Parsing Efficiency," KIPS Transactions on Software and Data Engineering, vol. 5, no. 1, pp. 21-28, 2016. DOI: 10.3745/KTSDE.2016.5.1.21.

[ACM Style]
Sung Dong Kim. 2016. Three-Phase English Syntactic Analysis for Improving the Parsing Efficiency. KIPS Transactions on Software and Data Engineering, 5, 1, (2016), 21-28. DOI: 10.3745/KTSDE.2016.5.1.21.