Graph Based Network with Contextualized Representations of Turns in Dialogue

Bongseok Lee, Yong Suk Choi


Abstract
Dialogue-based relation extraction (RE) aims to extract relation(s) between two arguments that appear in a dialogue. Because dialogues have the characteristics of high personal pronoun occurrences and low information density, and since most relational facts in dialogues are not supported by any single sentence, dialogue-based relation extraction requires a comprehensive understanding of dialogue. In this paper, we propose the TUrn COntext awaRE Graph Convolutional Network (TUCORE-GCN) modeled by paying attention to the way people understand dialogues. In addition, we propose a novel approach which treats the task of emotion recognition in conversations (ERC) as a dialogue-based RE. Experiments on a dialogue-based RE dataset and three ERC datasets demonstrate that our model is very effective in various dialogue-based natural language understanding tasks. In these experiments, TUCORE-GCN outperforms the state-of-the-art models on most of the benchmark datasets. Our code is available at https://github.com/BlackNoodle/TUCORE-GCN.
Anthology ID:
2021.emnlp-main.36
Volume:
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
Month:
November
Year:
2021
Address:
Online and Punta Cana, Dominican Republic
Editors:
Marie-Francine Moens, Xuanjing Huang, Lucia Specia, Scott Wen-tau Yih
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
443–455
Language:
URL:
https://aclanthology.org/2021.emnlp-main.36
DOI:
10.18653/v1/2021.emnlp-main.36
Bibkey:
Cite (ACL):
Bongseok Lee and Yong Suk Choi. 2021. Graph Based Network with Contextualized Representations of Turns in Dialogue. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 443–455, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.
Cite (Informal):
Graph Based Network with Contextualized Representations of Turns in Dialogue (Lee & Choi, EMNLP 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.emnlp-main.36.pdf
Video:
 https://aclanthology.org/2021.emnlp-main.36.mp4
Code
 blacknoodle/tucore-gcn
Data
DailyDialogDialogREEmoryNLPMELD