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We present an overview of the CLEF-2018 CheckThat! Lab on AutomaticIdentification and Verification of Political Claims, with focus on Task 1:Check-Worthiness. The task asks to predict which claims in a political debateshould be prioritized for fact-checking. In particular, given a debate or apolitical speech, the goal was to produce a ranked list of its sentences basedon their worthiness for fact checking. We offered the task in both English andArabic, based on debates from the 2016 US Presidential Campaign, as well as onsome speeches during and after the campaign. A total of 30 teams registered toparticipate in the Lab and seven teams actually submitted systems for Task~1.The most successful approaches used by the participants relied on recurrent andmulti-layer neural networks, as well as on combinations of distributionalrepresentations, on matchings claims' vocabulary against lexicons, and onmeasures of syntactic dependency. The best systems achieved mean averageprecision of 0.18 and 0.15 on the English and on the Arabic test datasets,respectively. This leaves large room for further improvement, and thus werelease all datasets and the scoring scripts, which should enable furtherresearch in check-worthiness estimation.

Overview of the CLEF-2018 CheckThat! Lab on Automatic Identification and Verification of Political Claims. Task 1: Check-Worthiness