Abstract
While reading financial documents, investors need to know the causes and their effects. This empowers them to make data-driven decisions. Thus, there is a need to develop an automated system for extracting causes and their effects from financial texts using Natural Language Processing. In this paper, we present the approach our team LIPI followed while participating in the FinCausal 2022 shared task. This approach is based on the winning solution of the first edition of FinCausal held in the year 2020.- Anthology ID:
- 2022.fnp-1.20
- Volume:
- Proceedings of the 4th Financial Narrative Processing Workshop @LREC2022
- Month:
- June
- Year:
- 2022
- Address:
- Marseille, France
- Editors:
- Mahmoud El-Haj, Paul Rayson, Nadhem Zmandar
- Venue:
- FNP
- SIG:
- Publisher:
- European Language Resources Association
- Note:
- Pages:
- 121–123
- Language:
- URL:
- https://aclanthology.org/2022.fnp-1.20
- DOI:
- Cite (ACL):
- Sohom Ghosh and Sudip Naskar. 2022. LIPI at FinCausal 2022: Mining Causes and Effects from Financial Texts. In Proceedings of the 4th Financial Narrative Processing Workshop @LREC2022, pages 121–123, Marseille, France. European Language Resources Association.
- Cite (Informal):
- LIPI at FinCausal 2022: Mining Causes and Effects from Financial Texts (Ghosh & Naskar, FNP 2022)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2022.fnp-1.20.pdf
- Code
- sohomghosh/cepn