Event Causality Identification - Shared Task 3, CASE 2023

Tan, Fiona Anting and Hettiarachchi, Hansi and Hürriyetoğlu, Ali and Oostdijk, Nelleke and Uca, Onur and Thapa, Surendrabikram and Liza, Farhana Ferdousi (2023) Event Causality Identification - Shared Task 3, CASE 2023. In: Proceedings of the 6th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text :. INCOMA Ltd, Shoumen, Bulgaria, pp. 144-150. ISBN 9789544520892

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Abstract

The Event Causality Identification Shared Task of CASE 2023 is the second iteration of a shared task centered around the Causal News Corpus. Two subtasks were involved: In Subtask 1, participants were challenged to predict if a sentence contains a causal relation or not. In Subtask 2, participants were challenged to identify the Cause, Effect, and Signal spans given an input causal sentence. For both subtasks, participants uploaded their predictions for a held-out test set, and ranking was done based on binary F1 and macro F1 scores for Subtask 1 and 2, respectively. This paper includes an overview of the work of the ten teams that submitted their results to our competition and the six system description papers that were received. The highest F1 scores achieved for Subtask 1 and 2 were 84.66% and 72.79%, respectively.

Item Type:
Contribution in Book/Report/Proceedings
Uncontrolled Keywords:
Research Output Funding/no_not_funded
Subjects:
?? no - not funded ??
ID Code:
221723
Deposited By:
Deposited On:
27 May 2025 13:55
Refereed?:
Yes
Published?:
Published
Last Modified:
27 May 2025 13:55