Standard
Event Causality Identification with Causal News Corpus - Shared Task 3, CASE 2022. / Tan, Fiona Anting
; Hettiarachchi, Hansi; Hürriyetoğlu, Ali et al.
Proceedings of the 5th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE). ed. / Ali Hürriyetoğlu; Hristo Tanev; Vanni Zavarella; Erdem Yörük. Association for Computational Linguistics, 2022. p. 195-208.
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Harvard
Tan, FA
, Hettiarachchi, H, Hürriyetoğlu, A, Caselli, T, Uca, O, Liza, FF & Oostdijk, N 2022,
Event Causality Identification with Causal News Corpus - Shared Task 3, CASE 2022. in A Hürriyetoğlu, H Tanev, V Zavarella & E Yörük (eds),
Proceedings of the 5th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE). Association for Computational Linguistics, pp. 195-208.
https://doi.org/10.18653/v1/2022.case-1.28APA
Tan, F. A.
, Hettiarachchi, H., Hürriyetoğlu, A., Caselli, T., Uca, O., Liza, F. F., & Oostdijk, N. (2022).
Event Causality Identification with Causal News Corpus - Shared Task 3, CASE 2022. In A. Hürriyetoğlu, H. Tanev, V. Zavarella, & E. Yörük (Eds.),
Proceedings of the 5th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE) (pp. 195-208). Association for Computational Linguistics.
https://doi.org/10.18653/v1/2022.case-1.28Vancouver
Tan FA
, Hettiarachchi H, Hürriyetoğlu A, Caselli T, Uca O, Liza FF et al.
Event Causality Identification with Causal News Corpus - Shared Task 3, CASE 2022. In Hürriyetoğlu A, Tanev H, Zavarella V, Yörük E, editors, Proceedings of the 5th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE). Association for Computational Linguistics. 2022. p. 195-208 doi: 10.18653/v1/2022.case-1.28
Author
Bibtex
@inproceedings{87cd8b1712814d41ade375f15342791e,
title = "Event Causality Identification with Causal News Corpus - Shared Task 3, CASE 2022",
abstract = "The Event Causality Identification Shared Task of CASE 2022 involved two subtasks working on the Causal News Corpus. Subtask 1 required participants to predict if a sentence contains a causal relation or not. This is a supervised binary classification task. Subtask 2 required participants to identify the Cause, Effect and Signal spans per causal sentence. This could be seen as a supervised sequence labeling task. 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 summarizes the work of the 17 teams that submitted their results to our competition and 12 system description papers that were received. The best F1 scores achieved for Subtask 1 and 2 were 86.19% and 54.15%, respectively. All the top-performing approaches involved pre-trained language models fine-tuned to the targeted task. We further discuss these approaches and analyze errors across participants{\textquoteright} systems in this paper.",
author = "Tan, {Fiona Anting} and Hansi Hettiarachchi and Ali H{\"u}rriyetoğlu and Tommaso Caselli and Onur Uca and Liza, {Farhana Ferdousi} and Nelleke Oostdijk",
year = "2022",
month = dec,
day = "7",
doi = "10.18653/v1/2022.case-1.28",
language = "English",
pages = "195--208",
editor = "Ali H{\"u}rriyetoğlu and Hristo Tanev and Vanni Zavarella and Erdem Y{\"o}r{\"u}k",
booktitle = "Proceedings of the 5th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE)",
publisher = "Association for Computational Linguistics",
}
RIS
TY - GEN
T1 - Event Causality Identification with Causal News Corpus - Shared Task 3, CASE 2022
AU - Tan, Fiona Anting
AU - Hettiarachchi, Hansi
AU - Hürriyetoğlu, Ali
AU - Caselli, Tommaso
AU - Uca, Onur
AU - Liza, Farhana Ferdousi
AU - Oostdijk, Nelleke
PY - 2022/12/7
Y1 - 2022/12/7
N2 - The Event Causality Identification Shared Task of CASE 2022 involved two subtasks working on the Causal News Corpus. Subtask 1 required participants to predict if a sentence contains a causal relation or not. This is a supervised binary classification task. Subtask 2 required participants to identify the Cause, Effect and Signal spans per causal sentence. This could be seen as a supervised sequence labeling task. 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 summarizes the work of the 17 teams that submitted their results to our competition and 12 system description papers that were received. The best F1 scores achieved for Subtask 1 and 2 were 86.19% and 54.15%, respectively. All the top-performing approaches involved pre-trained language models fine-tuned to the targeted task. We further discuss these approaches and analyze errors across participants’ systems in this paper.
AB - The Event Causality Identification Shared Task of CASE 2022 involved two subtasks working on the Causal News Corpus. Subtask 1 required participants to predict if a sentence contains a causal relation or not. This is a supervised binary classification task. Subtask 2 required participants to identify the Cause, Effect and Signal spans per causal sentence. This could be seen as a supervised sequence labeling task. 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 summarizes the work of the 17 teams that submitted their results to our competition and 12 system description papers that were received. The best F1 scores achieved for Subtask 1 and 2 were 86.19% and 54.15%, respectively. All the top-performing approaches involved pre-trained language models fine-tuned to the targeted task. We further discuss these approaches and analyze errors across participants’ systems in this paper.
U2 - 10.18653/v1/2022.case-1.28
DO - 10.18653/v1/2022.case-1.28
M3 - Conference contribution/Paper
SP - 195
EP - 208
BT - Proceedings of the 5th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text (CASE)
A2 - Hürriyetoğlu, Ali
A2 - Tanev, Hristo
A2 - Zavarella, Vanni
A2 - Yörük, Erdem
PB - Association for Computational Linguistics
ER -
