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Leveraging Semantic Representations Combined with Contextual Word Representations for Recognizing Textual Entailment in Vietnamese | | Quoc-Loc Duong
; Duc-Vu Nguyen
; Ngan Luu-Thuy Nguyen
; | | Date: |
1 Jan 2023 | | Abstract: | RTE is a significant problem and is a reasonably active research community.
The proposed research works on the approach to this problem are pretty diverse
with many different directions. For Vietnamese, the RTE problem is moderately
new, but this problem plays a vital role in natural language understanding
systems. Currently, methods to solve this problem based on contextual word
representation learning models have given outstanding results. However,
Vietnamese is a semantically rich language. Therefore, in this paper, we want
to present an experiment combining semantic word representation through the SRL
task with context representation of BERT relative models for the RTE problem.
The experimental results give conclusions about the influence and role of
semantic representation on Vietnamese in understanding natural language. The
experimental results show that the semantic-aware contextual representation
model has about 1% higher performance than the model that does not incorporate
semantic representation. In addition, the effects on the data domain in
Vietnamese are also higher than those in English. This result also shows the
positive influence of SRL on RTE problem in Vietnamese. | | Source: | arXiv, 2301.00422 | | Services: | Forum | Review | PDF | Favorites | |
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