Abstract
This paper presents an experimental study in Vietnamese constituency syntactic parsing. We first compare results of two recent constituency parsers on a Vietnamese corpus, a shift-reduce constituency parser and a neural parser. We then integrate distributed word representations into the shift-reduce parser to improve its \(F_1\) score. We also report a new state-of-the-art parsing score for Vietnamese with \(F_1\) score of 80% in the neural parser. Finally, we perform error analysis on a sample of 100 sentences for the neural parser, which helps categorize ambiguous and difficult constructions inherent to the problem of Vietnamese syntactic parsing.
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Notes
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VLSP Project, https://vlsp.hpda.vn/demo/.
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- 3.
Bidirectional Encoder Representations from Transformers.
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Nguyen-Thi, L., Le-Hong, P. (2020). An Experimental Study on Constituency Parsing for Vietnamese. In: Nguyen, LM., Phan, XH., Hasida, K., Tojo, S. (eds) Computational Linguistics. PACLING 2019. Communications in Computer and Information Science, vol 1215. Springer, Singapore. https://doi.org/10.1007/978-981-15-6168-9_30
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DOI: https://doi.org/10.1007/978-981-15-6168-9_30
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