BUT-FIT at SemEval-2020 Task 5: Automatic detection of counterfactual statements with deep pre-trained language representation models
2020-07-28SEMEVALCode Available0· sign in to hype
Martin Fajcik, Josef Jon, Martin Docekal, Pavel Smrz
Code Available — Be the first to reproduce this paper.
ReproduceCode
- github.com/MFajcik/SemEval_2020_Task-5OfficialIn paperpytorch★ 1
Abstract
This paper describes BUT-FIT's submission at SemEval-2020 Task 5: Modelling Causal Reasoning in Language: Detecting Counterfactuals. The challenge focused on detecting whether a given statement contains a counterfactual (Subtask 1) and extracting both antecedent and consequent parts of the counterfactual from the text (Subtask 2). We experimented with various state-of-the-art language representation models (LRMs). We found RoBERTa LRM to perform the best in both subtasks. We achieved the first place in both exact match and F1 for Subtask 2 and ranked second for Subtask 1.