Publication Details

BUT-FIT at SemEval-2020 Task 5: Automatic detection of counterfactual statements with deep pre-trained language representation models

FAJČÍK, M.; DOČEKAL, M.; JON, J.; SMRŽ, P. BUT-FIT at SemEval-2020 Task 5: Automatic detection of counterfactual statements with deep pre-trained language representation models. In Proceedings of the Fourteenth Workshop on Semantic Evaluation. Barcelona (online): Association for Computational Linguistics, 2020. p. 437-444. ISBN: 978-1-952148-31-6.
Czech title
BUT-FIT na SemEval-2020 Task 5: Automatická detekce kontrafaktuálních výrazů s použitím hlubokých předtrénovaných modelů
Type
conference paper
Language
English
Authors
Fajčík Martin, Ing., Ph.D. (DCGM)
Dočekal Martin, Ing. (DCGM)
Jon Josef, Ing.
Smrž Pavel, doc. RNDr., Ph.D. (DCGM)
URL
Keywords

counterfactual, counterfactual reasoning, BERT, RoBERTa, ALBERT, causal reasoning, what-if, semeval, classification, extraction

Abstract

This paper describes BUT-FITs 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.

Published
2020
Pages
437–444
Proceedings
Proceedings of the Fourteenth Workshop on Semantic Evaluation
Conference
The 28th International Conference on Computational Linguistics, Barcelona (online), ES
ISBN
978-1-952148-31-6
Publisher
Association for Computational Linguistics
Place
Barcelona (online)
UT WoS
001361895500053
EID Scopus
2-s2.0-85123298637
BibTeX 
@inproceedings{BUT168151,
  author="Martin {Fajčík} and Martin {Dočekal} and Josef {Jon} and Pavel {Smrž}",
  title="BUT-FIT at SemEval-2020 Task 5: Automatic detection of counterfactual statements with deep pre-trained language representation models",
  booktitle="Proceedings of the Fourteenth Workshop on Semantic Evaluation",
  year="2020",
  pages="437--444",
  publisher="Association for Computational Linguistics",
  address="Barcelona (online)",
  isbn="978-1-952148-31-6",
  url="https://www.aclweb.org/anthology/2020.semeval-1.53/"
}
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