SemEval-2022 Task 3: PreTENS - Evaluating Neural Networks on Presuppositional Semantic Knowledge

Roberto Zamparelli, Shammur A. Chowdhury, Dominique Brunato, Cristiano Chesi, Felice Dell'Orletta, Arid Hasan, Giulia Venturi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Citations (Scopus)

Abstract

We report the results of the SemEval 2022 Task 3, PreTENS, on evaluation the acceptability of simple sentences containing constructions whose two arguments are presupposed to be or not to be in an ordered taxonomic relation. The task featured two sub-tasks articulated as: (i) binary prediction task and (ii) regression task, predicting the acceptability in a continuous scale. The sentences were artificially generated in three languages (English, Italian and French). 21 systems, with 8 system papers were submitted for the task, all based on various types of fine-tuned transformer systems, often with ensemble methods and various data augmentation techniques. The best systems reached an F1-macro score of 94.49 (sub-task1) and a Spearman correlation coefficient of 0.80 (sub-task2), with interesting variations in specific constructions and/or languages.

Original languageEnglish
Title of host publicationSemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop
EditorsGuy Emerson, Natalie Schluter, Gabriel Stanovsky, Ritesh Kumar, Alexis Palmer, Nathan Schneider, Siddharth Singh, Shyam Ratan
PublisherAssociation for Computational Linguistics (ACL)
Pages228-238
Number of pages11
ISBN (Electronic)9781955917803
Publication statusPublished - 2022
Event16th International Workshop on Semantic Evaluation, SemEval 2022 - Seattle, United States
Duration: 14 Jul 202215 Jul 2022

Publication series

NameSemEval 2022 - 16th International Workshop on Semantic Evaluation, Proceedings of the Workshop

Conference

Conference16th International Workshop on Semantic Evaluation, SemEval 2022
Country/TerritoryUnited States
CitySeattle
Period14/07/2215/07/22

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