@inproceedings{tan-etal-2023-event-causality,
title = "Event Causality Identification - Shared Task 3, {CASE} 2023",
author = {Tan, Fiona Anting and
Hettiarachchi, Hansi and
H{\"u}rriyeto{\u{g}}lu, Ali and
Oostdijk, Nelleke and
Uca, Onur and
Thapa, Surendrabikram and
Liza, Farhana Ferdousi},
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-1.19",
pages = "144--150",
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.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="tan-etal-2023-event-causality">
<titleInfo>
<title>Event Causality Identification - Shared Task 3, CASE 2023</title>
</titleInfo>
<name type="personal">
<namePart type="given">Fiona</namePart>
<namePart type="given">Anting</namePart>
<namePart type="family">Tan</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Hansi</namePart>
<namePart type="family">Hettiarachchi</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Ali</namePart>
<namePart type="family">Hürriyetoğlu</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Nelleke</namePart>
<namePart type="family">Oostdijk</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Onur</namePart>
<namePart type="family">Uca</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Surendrabikram</namePart>
<namePart type="family">Thapa</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Farhana</namePart>
<namePart type="given">Ferdousi</namePart>
<namePart type="family">Liza</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2023-09</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 6th Workshop on Challenges and Applications of Automated Extraction of Socio-political Events from Text</title>
</titleInfo>
<name type="personal">
<namePart type="given">Ali</namePart>
<namePart type="family">Hürriyetoğlu</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Hristo</namePart>
<namePart type="family">Tanev</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Vanni</namePart>
<namePart type="family">Zavarella</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Reyyan</namePart>
<namePart type="family">Yeniterzi</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Erdem</namePart>
<namePart type="family">Yörük</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Milena</namePart>
<namePart type="family">Slavcheva</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>INCOMA Ltd., Shoumen, Bulgaria</publisher>
<place>
<placeTerm type="text">Varna, Bulgaria</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<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.</abstract>
<identifier type="citekey">tan-etal-2023-event-causality</identifier>
<location>
<url>https://aclanthology.org/2023.case-1.19</url>
</location>
<part>
<date>2023-09</date>
<extent unit="page">
<start>144</start>
<end>150</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Event Causality Identification - Shared Task 3, CASE 2023
%A Tan, Fiona Anting
%A Hettiarachchi, Hansi
%A Hürriyetoğlu, Ali
%A Oostdijk, Nelleke
%A Uca, Onur
%A Thapa, Surendrabikram
%A Liza, Farhana Ferdousi
%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 tan-etal-2023-event-causality
%X 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.
%U https://aclanthology.org/2023.case-1.19
%P 144-150
Markdown (Informal)
[Event Causality Identification - Shared Task 3, CASE 2023](https://aclanthology.org/2023.case-1.19) (Tan et al., CASE-WS 2023)
ACL
- Fiona Anting Tan, Hansi Hettiarachchi, Ali Hürriyetoğlu, Nelleke Oostdijk, Onur Uca, Surendrabikram Thapa, and Farhana Ferdousi Liza. 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, pages 144–150, Varna, Bulgaria. INCOMA Ltd., Shoumen, Bulgaria.