Domino at FinCausal 2020, Task 1 and 2: Causal Extraction System
Sharanya Chakravarthy, Tushar Kanakagiri, Karthik Radhakrishnan, Anjana Umapathy
Abstract
Automatic identification of cause-effect relationships from data is a challenging but important problem in artificial intelligence. Identifying semantic relationships has become increasingly important for multiple downstream applications like Question Answering, Information Retrieval and Event Prediction. In this work, we tackle the problem of causal relationship extraction from financial news using the FinCausal 2020 dataset. We tackle two tasks - 1) Detecting the presence of causal relationships and 2) Extracting segments corresponding to cause and effect from news snippets. We propose Transformer based sequence and token classification models with post-processing rules which achieve an F1 score of 96.12 and 79.60 on Tasks 1 and 2 respectively.- Anthology ID:
- 2020.fnp-1.15
- Volume:
- Proceedings of the 1st Joint Workshop on Financial Narrative Processing and MultiLing Financial Summarisation
- Month:
- December
- Year:
- 2020
- Address:
- Barcelona, Spain (Online)
- Editors:
- Dr Mahmoud El-Haj, Dr Vasiliki Athanasakou, Dr Sira Ferradans, Dr Catherine Salzedo, Dr Ans Elhag, Dr Houda Bouamor, Dr Marina Litvak, Dr Paul Rayson, Dr George Giannakopoulos, Nikiforos Pittaras
- Venue:
- FNP
- SIG:
- Publisher:
- COLING
- Note:
- Pages:
- 90–94
- Language:
- URL:
- https://aclanthology.org/2020.fnp-1.15
- DOI:
- Cite (ACL):
- Sharanya Chakravarthy, Tushar Kanakagiri, Karthik Radhakrishnan, and Anjana Umapathy. 2020. Domino at FinCausal 2020, Task 1 and 2: Causal Extraction System. In Proceedings of the 1st Joint Workshop on Financial Narrative Processing and MultiLing Financial Summarisation, pages 90–94, Barcelona, Spain (Online). COLING.
- Cite (Informal):
- Domino at FinCausal 2020, Task 1 and 2: Causal Extraction System (Chakravarthy et al., FNP 2020)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2020.fnp-1.15.pdf
- Code
- sharanyarc96/domino-fincausal2020
- Data
- SQuAD