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2020 COLING COLING 2020

LIORI at the FinCausal 2020 Shared task

Abstract

AbstractIn this paper, we describe the results of team LIORI at the FinCausal 2020 Shared task held as a part of the 1st Joint Workshop on Financial Narrative Processing and MultiLingual Financial Summarisation. The shared task consisted of two subtasks: classifying whether a sentence contains any causality and labelling phrases that indicate causes and consequences. Our team ranked 1st in the first subtask and 4th in the second one. We used Transformer-based models with joint-task learning and their ensembles.

🧭 Keyword Pioneer — joint-task learning
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio

Authors

Denis Gordeev , Adis Davletov , Alexey Rey , Nikolay Arefiev

Topics

Natural Language Processing > Applications > Information Extraction Natural Language Processing > Resources & Methods > Large Language Models

Keywords

ensemble learning sequence labeling transformer-based model causality detection joint-task learning
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