Abstract
This paper describes FinSim4-ESG 1 shared task organized in the 4th FinNLP workshopwhich is held in conjunction with the IJCAI-ECAI-2022 confer- enceThis year, the FinSim4 is extended to the Environment, Social and Government (ESG) insights and proposes two subtasks, one for ESG Taxonomy Enrichment and the other for Sustainable Sentence Prediction. Among the 28 teams registered to the shared task, a total of 8 teams submitted their systems results and 6 teams also submitted a paper to describe their method. The winner of each subtask shows good performance results of 0.85% and 0.95% in terms of accuracy, respectively.- Anthology ID:
- 2022.finnlp-1.28
- Volume:
- Proceedings of the Fourth Workshop on Financial Technology and Natural Language Processing (FinNLP)
- Month:
- December
- Year:
- 2022
- Address:
- Abu Dhabi, United Arab Emirates (Hybrid)
- Editors:
- Chung-Chi Chen, Hen-Hsen Huang, Hiroya Takamura, Hsin-Hsi Chen
- Venue:
- FinNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 211–217
- Language:
- URL:
- https://aclanthology.org/2022.finnlp-1.28
- DOI:
- 10.18653/v1/2022.finnlp-1.28
- Cite (ACL):
- Juyeon Kang and Ismail El Maarouf. 2022. FinSim4-ESG Shared Task: Learning Semantic Similarities for the Financial Domain. Extended edition to ESG insights. In Proceedings of the Fourth Workshop on Financial Technology and Natural Language Processing (FinNLP), pages 211–217, Abu Dhabi, United Arab Emirates (Hybrid). Association for Computational Linguistics.
- Cite (Informal):
- FinSim4-ESG Shared Task: Learning Semantic Similarities for the Financial Domain. Extended edition to ESG insights (Kang & El Maarouf, FinNLP 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2022.finnlp-1.28.pdf