  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.
