An Attempt to Develop a Neural Parser Based on Simplified Head-Driven Phrase Structure Grammar on Vietnamese

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F26%3AFMFGBNBB" target="_blank" >RIV/00216208:11320/26:FMFGBNBB - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1007/978-981-96-4282-3_26" target="_blank" >http://dx.doi.org/10.1007/978-981-96-4282-3_26</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-981-96-4282-3_26" target="_blank" >10.1007/978-981-96-4282-3_26</a>

Result language

angličtina

Original language name

An Attempt to Develop a Neural Parser Based on Simplified Head-Driven Phrase Structure Grammar on Vietnamese

Original language description

In this paper, we aimed to develop a neural parser for Vietnamese based on simplified Head-Driven Phrase Structure Grammar (HPSG). The existing corpora, VietTreebank and VnDT, had around 15% of constituency and dependency tree pairs that did not adhere to simplified HPSG rules. To attempt to address the issue of the corpora not adhering to simplified HPSG rules, we randomly permuted samples from the training and development sets to make them compliant with simplified HPSG. We then modified the first simplified HPSG Neural Parser for the Penn Treebank by replacing it with the PhoBERT or XLM-RoBERTa models, which can encode Vietnamese texts. We conducted experiments on our modified VietTreebank and VnDT corpora. Our extensive experiments showed that the simplified HPSG Neural Parser achieved a new state-of-the-art F-score of 82% for constituency parsing when using the same predicted part-of-speech (POS) tags as the self-attentive constituency parser. Additionally, it outperformed previous studies in dependency parsing with a higher Unlabeled Attachment Score (UAS). However, our parser obtained lower Labeled Attachment Score (LAS) scores likely due to our focus on arc permutation without changing the original labels, as we did not consult with a linguistic expert. Lastly, the research findings of this paper suggest that simplified HPSG should be given more attention to linguistic expert when developing treebanks for Vietnamese natural language processing. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

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Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Commun. Comput. Info. Sci.

ISBN

978-981-96-4281-6

ISSN

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e-ISSN

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Number of pages

16

Pages from-to

313-328

Publisher name

Springer Science and Business Media Deutschland GmbH

Place of publication

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Event location

Danang

Event date

Jan 1, 2026

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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