@inproceedings{schrader-etal-2023-boschai,
title = "{B}osch{AI} @ Causal News Corpus 2023: Robust Cause-Effect Span Extraction using Multi-Layer Sequence Tagging and Data Augmentation",
author = "Schrader, Timo Pierre and
Razniewski, Simon and
Lange, Lukas and
Friedrich, Annemarie",
editor = {H{\"u}rriyeto{\u{g}}lu, Ali and
Tanev, Hristo and
Zavarella, Vanni and
Yeniterzi, Reyyan and
Y{\"o}r{\"u}k, Erdem and
Slavcheva, Milena},
booktitle = "Proceedings of the 6th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text",
month = sep,
year = "2023",
address = "Varna, Bulgaria",
publisher = "INCOMA Ltd., Shoumen, Bulgaria",
url = "https://aclanthology.org/2023.case-1.5",
pages = "38--43",
abstract = "Understanding causality is a core aspect of intelligence. The Event Causality Identification with Causal News Corpus Shared Task addresses two aspects of this challenge: Subtask 1 aims at detecting causal relationships in texts, and Subtask 2 requires identifying signal words and the spans that refer to the cause or effect, respectively. Our system, which is based on pre-trained transformers, stacked sequence tagging, and synthetic data augmentation, ranks third in Subtask 1 and wins Subtask 2 with an F1 score of 72.8, corresponding to a margin of 13 pp. to the second-best system.",
}
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%0 Conference Proceedings
%T BoschAI @ Causal News Corpus 2023: Robust Cause-Effect Span Extraction using Multi-Layer Sequence Tagging and Data Augmentation
%A Schrader, Timo Pierre
%A Razniewski, Simon
%A Lange, Lukas
%A Friedrich, Annemarie
%Y Hürriyetoğlu, Ali
%Y Tanev, Hristo
%Y Zavarella, Vanni
%Y Yeniterzi, Reyyan
%Y Yörük, Erdem
%Y Slavcheva, Milena
%S Proceedings of the 6th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text
%D 2023
%8 September
%I INCOMA Ltd., Shoumen, Bulgaria
%C Varna, Bulgaria
%F schrader-etal-2023-boschai
%X Understanding causality is a core aspect of intelligence. The Event Causality Identification with Causal News Corpus Shared Task addresses two aspects of this challenge: Subtask 1 aims at detecting causal relationships in texts, and Subtask 2 requires identifying signal words and the spans that refer to the cause or effect, respectively. Our system, which is based on pre-trained transformers, stacked sequence tagging, and synthetic data augmentation, ranks third in Subtask 1 and wins Subtask 2 with an F1 score of 72.8, corresponding to a margin of 13 pp. to the second-best system.
%U https://aclanthology.org/2023.case-1.5
%P 38-43
Markdown (Informal)
[BoschAI @ Causal News Corpus 2023: Robust Cause-Effect Span Extraction using Multi-Layer Sequence Tagging and Data Augmentation](https://aclanthology.org/2023.case-1.5) (Schrader et al., CASE-WS 2023)
ACL