VerbNet Dataset
In our experiments, we achieved the prototype of the Thai VerbNet corpus and along with our method, they provide the baseline and benchmark for future work.
Thammasat University
Thailand
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Lexical resources have played a key role in advancing natural language processing research. One particular resource is VerbNet, which contains both syntactic and semantic information of verbs. However, the construction of lexical resources, especially for Thai VerbNet, are infeasible without a suitable tool to support the construction due to the complexity and laboriousness of the labeling task. In this work, we introduce the system for annotation and managing lexical resources, especially for FrameNet and VerbNet, to help facilitate the construction of lexical resources. This work presents an attempt to construct the first version of a Thai VerbNet corpus via data enrichment of the existing lexical resource. The algorithms for semantic role labeling are surveyed and the algorithm for verb classification is invented to facilitate the construction of the lexical resources. In our experiments, we achieved the prototype of the Thai VerbNet corpus and along with our method, they provide the baseline and benchmark for future work.
In our experiments, we achieved the prototype of the Thai VerbNet corpus and along with our method, they provide the baseline and benchmark for future work.
BibTex
@article{10.1145/3638533,
author = {Chungnoi, Krittanut and Kongkachandra, Rachada and Gulyanon, Sarun},
title = {The Computational Method for Supporting Thai VerbNet Construction},
year = {2024},
issue_date = {February 2024},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
volume = {23},
number = {2},
issn = {2375-4699},
url = {https://doi.org/10.1145/3638533},
doi = {10.1145/3638533},
journal = {ACM Trans. Asian Low-Resour. Lang. Inf. Process.},
month = {feb},
articleno = {22},
numpages = {15}
}