arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2007.07997cs.CLcs.IRcs.LG

Overview of CheckThat! 2020: Automatic Identification and Verification of Claims in Social Media

Università di Bologna(博洛尼亚大学);Qatar University(卡塔尔大学);Qatar Computing Research Institute, HBKU(卡塔尔计算研究所(哈马德·本·哈利法大学));Sofia University “St Kliment Ohridski”(索菲亚大学“圣克莱门特·奥赫里德斯基”)
Alberto Barron-Cedeno, Tamer Elsayed, Preslav Nakov, Giovanni Da San Martino, Maram Hasanain, Reem Suwaileh, Fatima Haouari, Nikolay Babulkov, Bayan Hamdan, Ale… 展开作者

Alberto Barron-Cedeno, Tamer Elsayed, Preslav Nakov, Giovanni Da San Martino, Maram Hasanain, Reem Suwaileh, Fatima Haouari, Nikolay Babulkov, Bayan Hamdan, Alex Nikolov, Shaden Shaar, Zien Sheikh Ali

英文摘要:

We present an overview of the third edition of the CheckThat! Lab at CLEF 2020. The lab featured five tasks in two different languages: English and Arabic. The first four tasks compose the full pipeline of claim verification in social media: Task 1 on check-worthiness estimation, Task 2 on retrieving previously fact-checked claims, Task 3 on evidence retrieval, and Task 4 on claim verification. The lab is completed with Task 5 on check-worthiness estimation in political debates and speeches. A total of 67 teams registered to participate in the lab (up from 47 at CLEF 2019), and 23 of them actually submitted runs (compared to 14 at CLEF 2019). Most teams used deep neural networks based on BERT, LSTMs, or CNNs, and achieved sizable improvements over the baselines on all tasks. Here we describe the tasks setup, the evaluation results, and a summary of the approaches used by the participants, and we discuss some lessons learned. Last but not least, we release to the research community all datasets from the lab as well as the evaluation scripts, which should enable further research in the important tasks of check-worthiness estimation and automatic claim verification.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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