| アイテムタイプ |
会議発表論文 / Conference Paper(1) |
| 公開日 |
2025-06-03 |
| タイトル |
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タイトル |
Overview of #SMM4H 2024 $2013 Task 2: Cross-Lingual Few-Shot Relation Extraction for Pharmacovigilance in French, German, and Japanese |
| 言語 |
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言語 |
eng |
| 資源タイプ |
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資源タイプ |
conference paper |
| アクセス権 |
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アクセス権 |
open access |
| 著者 |
Raithel, Lisa
Thomas, Philippe
Verma, Bhuvanesh
Roller, Roland
Yeh, Hui-Syuan
矢田, 竣太郎
Grouin, Cyril
若宮, 翔子
荒牧, 英治
M$00F6ller, Sebastian
Zweigenbaum, Pierre
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| 抄録 |
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内容記述タイプ |
Abstract |
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内容記述 |
This paper provides an overview of Task 2 from the Social Media Mining for Health 2024 shared task (#SMM4H 2024), which focused on Named Entity Recognition (NER, Subtask 2a) and the joint task of NER and Relation Extraction (RE, Subtask 2b) for detecting adverse drug reactions (ADRs) in German, Japanese, and French texts written by patients. Participants were challenged with a few-shot learning scenario, necessitating models that can effectively generalize from limited annotated examples. Despite the diverse strategies employed by the participants, the overall performance across submissions from three teams highlighted significant challenges. The results underscored the complexity of extracting entities and relations in multi-lingual contexts, especially from the noisy and informal nature of user-generated content. Further research is required to develop robust systems capable of accurately identifying and associating ADR-related information in low-resource and multilingual settings. |
| 書誌情報 |
en : Proceedings of the 9th Social Media Mining for Health Research and Applications (SMM4H 2024) Workshop and Shared Tasks
p. 170-182,
発行日 2024-08-15
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| 会議情報 |
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会議名 |
In Proceedings of the 9th Social Media Mining for Health Research and Applications Workshop and Shared Tasks (#SMM4H 2024) |
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開始年 |
2024 |
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開始月 |
08 |
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開始日 |
15 |
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終了年 |
2024 |
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終了月 |
08 |
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終了日 |
15 |
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開催地 |
Bangkok |
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開催国 |
THA |
| 出版者 |
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出版者 |
Association for Computational Linguistics |
| 出版者版URI |
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関連タイプ |
isReplacedBy |
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識別子タイプ |
URI |
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関連識別子 |
https://aclanthology.org/2024.smm4h-1.39/ |
| 権利 |
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権利情報Resource |
https://creativecommons.org/licenses/by/4.0/ |
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権利情報 |
$00A92024 Association for Computational Linguistics |
| 著者版フラグ |
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出版タイプ |
NA |
| 助成情報 |
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助成機関名 |
NCGM |
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研究課題番号 |
JPJ012425 |
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研究課題名 |
Cross-ministerial Strategic Innovation Promotion Program (SIP) on “Integrated Health Care System” |
| 助成情報 |
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助成機関名 |
Japan Science and Technology Agency(JST) |
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研究課題番号 |
JPMJCR20G9 |
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研究課題名 |
医薬品安全性監視のための言語を超えた知識強化情報抽出(KEEPHA) |
| 助成情報 |
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助成機関名 |
Agence Nationale de la Recherche(ANR) |
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研究課題番号 |
ANR-20-IADJ-0005-01 |
| 助成情報 |
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助成機関名 |
Deutsche Forschungsgemeinschaft (DFG) |
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研究課題番号 |
DFG-442445488 |
| 助成情報 |
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助成機関名 |
German Federal Ministry of Education and Research |
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研究課題番号 |
BIFOLD24B |
