Effective Use of Graph Convolution Network and Contextual Sub-Tree for Commodity News Event Extraction

Meisin Lee, Lay-Ki Soon, Eu-Gene Siew


Abstract
Event extraction in commodity news is a less researched area as compared to generic event extraction. However, accurate event extraction from commodity news is useful in abroad range of applications such as under-standing event chains and learning event-event relations, which can then be used for commodity price prediction. The events found in commodity news exhibit characteristics different from generic events, hence posing a unique challenge in event extraction using existing methods. This paper proposes an effective use of Graph Convolutional Networks(GCN) with a pruned dependency parse tree, termed contextual sub-tree, for better event ex-traction in commodity news. The event ex-traction model is trained using feature embed-dings from ComBERT, a BERT-based masked language model that was produced through domain-adaptive pre-training on a commodity news corpus. Experimental results show the efficiency of the proposed solution, which out-performs existing methods with F1 scores as high as 0.90. Furthermore, our pre-trained language model outperforms GloVe by 23%, and BERT and RoBERTa by 7% in terms of argument roles classification. For the goal of re-producibility, the code and trained models are made publicly available.
Anthology ID:
2021.econlp-1.10
Volume:
Proceedings of the Third Workshop on Economics and Natural Language Processing
Month:
November
Year:
2021
Address:
Punta Cana, Dominican Republic
Editors:
Udo Hahn, Veronique Hoste, Amanda Stent
Venue:
ECONLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
69–81
Language:
URL:
https://aclanthology.org/2021.econlp-1.10
DOI:
10.18653/v1/2021.econlp-1.10
Bibkey:
Cite (ACL):
Meisin Lee, Lay-Ki Soon, and Eu-Gene Siew. 2021. Effective Use of Graph Convolution Network and Contextual Sub-Tree for Commodity News Event Extraction. In Proceedings of the Third Workshop on Economics and Natural Language Processing, pages 69–81, Punta Cana, Dominican Republic. Association for Computational Linguistics.
Cite (Informal):
Effective Use of Graph Convolution Network and Contextual Sub-Tree for Commodity News Event Extraction (Lee et al., ECONLP 2021)
Copy Citation:
PDF:
https://preview.aclanthology.org/nschneid-patch-1/2021.econlp-1.10.pdf
Video:
 https://preview.aclanthology.org/nschneid-patch-1/2021.econlp-1.10.mp4
Code
 meisin/commodity-news-event-extraction