Fraunhofer IAIS at FinCausal 2020, Tasks 1 & 2: Using Ensemble Methods and Sequence Tagging to Detect Causality in Financial Documents

Maren Pielka, Rajkumar Ramamurthy, Anna Ladi, Eduardo Brito, Clayton Chapman, Paul Mayer, Rafet Sifa


Abstract
The FinCausal 2020 shared task aims to detect causality on financial news and identify those parts of the causal sentences related to the underlying cause and effect. We apply ensemble-based and sequence tagging methods for identifying causality, and extracting causal subsequences. Our models yield promising results on both sub-tasks, with the prospect of further improvement given more time and computing resources. With respect to task 1, we achieved an F1 score of 0.9429 on the evaluation data, and a corresponding ranking of 12/14. For task 2, we were ranked 6/10, with an F1 score of 0.76 and an ExactMatch score of 0.1912.
Anthology ID:
2020.fnp-1.10
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:
64–68
Language:
URL:
https://aclanthology.org/2020.fnp-1.10
DOI:
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Cite (ACL):
Maren Pielka, Rajkumar Ramamurthy, Anna Ladi, Eduardo Brito, Clayton Chapman, Paul Mayer, and Rafet Sifa. 2020. Fraunhofer IAIS at FinCausal 2020, Tasks 1 & 2: Using Ensemble Methods and Sequence Tagging to Detect Causality in Financial Documents. In Proceedings of the 1st Joint Workshop on Financial Narrative Processing and MultiLing Financial Summarisation, pages 64–68, Barcelona, Spain (Online). COLING.
Cite (Informal):
Fraunhofer IAIS at FinCausal 2020, Tasks 1 & 2: Using Ensemble Methods and Sequence Tagging to Detect Causality in Financial Documents (Pielka et al., FNP 2020)
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https://aclanthology.org/2020.fnp-1.10.pdf