ANDI @ CONcreTEXT: Predicting concreteness in context for English and Italian using distributional models and behavioural norms
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11 mai 2021
- doi: 10.4000/books.aaccademia.7465
- eisbn: 9791280136329
https://creativecommons.org/licenses/by-nc-nd/4.0/ , info:eu-repo/semantics/openAccess
Mots-clés
EVALITA COVID-19 Infodemic linguistica computazionale Automatic Misogyny Identification Misogyny on Twitter Posts AlBERTo Convolutional Neural Network BERT Model Hate Speech Detection Multimodal Meme Detection MEME management Language Game ``La Ghigliottina'' Language & Linguistics LAN000000 CBXSujets proches
Language (New words, slang, etc.) Women-hatingCiter ce document
Armand Stefan Rotaru, « ANDI @ CONcreTEXT: Predicting concreteness in context for English and Italian using distributional models and behavioural norms », Accademia University Press, ID : 10.4000/books.aaccademia.7465
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Résumé
In this paper we describe our participation in the CONcreTEXT task of EVALITA 2020, which involved predicting subjective ratings of concreteness for words presented in context. Our approach, which ranked first in both the English and Italian subtasks, relies on a combination of context-dependent and context-independent distributional models, together with behavioural norms. We show that good results can be obtained for Italian, by first automatically translating the Italian stimuli into English, and then using existing resources for both Italian and English.