SemEval-2021 Task 9: Fact Verification and Evidence Finding for Tabular Data in Scientific Documents (SEM-TAB-FACTS)

TL;DR

This paper introduces a new dataset and shared tasks for fact verification and evidence finding in scientific tables, highlighting the challenges and solutions in understanding tabular data for scientific document analysis.

Contribution

It presents a novel dataset with over 180K statements and 16M evidence annotations, and defines two sub-tasks for fact verification and evidence extraction in scientific tables.

Findings

69 teams participated in the shared task

19 teams submitted results for fact verification

12 teams submitted results for evidence finding

Abstract

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.