  Understanding tables is an important and relevant task that involves
understanding table structure as well as being able to compare and contrast
information within cells. In this paper, we address this challenge by
presenting a new dataset and tasks that addresses this goal in a shared task in
SemEval 2020 Task 9: Fact Verification and Evidence Finding for Tabular Data in
Scientific Documents (SEM-TAB-FACTS). Our dataset contains 981
manually-generated tables and an auto-generated dataset of 1980 tables
providing over 180K statement and over 16M evidence annotations. SEM-TAB-FACTS
featured two sub-tasks. In sub-task A, the goal was to determine if a statement
is supported, refuted or unknown in relation to a table. In sub-task B, the
focus was on identifying the specific cells of a table that provide evidence
for the statement. 69 teams signed up to participate in the task with 19
successful submissions to subtask A and 12 successful submissions to subtask B.
We present our results and main findings from the competition.
