ntust-nlp-2 at ROCLING-2021 Shared Task: BERT-based semantic analyzer with word-level information

988

Authors

nan

Abstract

AbstractIn this paper, we proposed a BERT-based dimensional semantic analyzer, which is designed by incorporating with word-level information. Our model achieved three of the best results in four metrics on “ROCLING 2021 Shared Task: Dimensional Sentiment Analysis for Educational Texts”. We conducted a series of experiments to compare the effectiveness of different pre-trained methods. Besides, the results also proofed that our method can significantly improve the performances than classic methods. Based on the experiments, we also discussed the impact of model architectures and datasets.

Keywords

nan

Full Content

�� The 33rd Conference on Computational Linguistics and Speech Processing (ROCLING 2021) Taoyuan, Taiwan, October 15-16, 2021. The Association for Computational Linguistics and Chinese Language Processing 360 � �� W {w��, w1, ..., w|T|, w��} �� w�� w�� = �� W � �� E = {e��, e1, ..., e|T|, e��}�� E �� w�� h�� H = ��(E) [yv, ya] = ��(h��) [yv, ya] �� Lt = ��([yv, ya], [ˆyv, ˆya]) ��ˆyv � ˆya �� …

Content truncated to 500 words

Labeled Text

Publication Details

Paper ID:: 988
Year:: 2021
Publication:: TIPSTER
Publication Type:: conf
DOI:: nan

Links

Paper URL PDF Publication URL