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

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F20%3APU138642" target="_blank" >RIV/00216305:26230/20:PU138642 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.aclweb.org/anthology/2020.semeval-1.53/" target="_blank" >https://www.aclweb.org/anthology/2020.semeval-1.53/</a>

  • DOI - Digital Object Identifier

Alternative languages

  • Result language

    angličtina

  • Original language name

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

  • Original language description

    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.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/LTC18006" target="_blank" >LTC18006: Large-Scale Information Extraction and Gamification for Crowdsourced Language Learning</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Others

  • Publication year

    2020

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Proceedings of the Fourteenth Workshop on Semantic Evaluation

  • ISBN

    978-1-952148-31-6

  • ISSN

  • e-ISSN

  • Number of pages

    8

  • Pages from-to

    437-444

  • Publisher name

    Association for Computational Linguistics

  • Place of publication

    Barcelona (online)

  • Event location

    Barcelona (online)

  • Event date

    Dec 8, 2020

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article