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Identification des Expressions Polylexicales dans les Tweets

Nicolas Zampieri 1 Carlos Ramisch 2 Irina Illina 1 Dominique Fohr 1 
1 MULTISPEECH - Speech Modeling for Facilitating Oral-Based Communication
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
2 TALEP - Traitement Automatique du Langage Ecrit et Parlé
LIS - Laboratoire d'Informatique et Systèmes
Abstract : Multiword expression (MWE) identification in tweets is a complex task due to the complex linguistic nature of MWEs combined with the non-standard language use on social networks. In this article, we present this related task on \nico{English} Twitter data. We compare the performance of two systems: lexicon-based and deep neural networks-based (DNN). We experimentally evaluate seven configurations of a state-of-the-art DNN system based on recurrent networks using pre-trained contextual embeddings from BERT. The DNN-based system outperforms the lexicon-based one thanks to its superior generalization power.
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https://hal.archives-ouvertes.fr/hal-03676506
Contributor : Nicolas Zampieri Connect in order to contact the contributor
Submitted on : Tuesday, May 24, 2022 - 9:22:07 AM
Last modification on : Monday, May 30, 2022 - 5:39:39 PM

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  • HAL Id : hal-03676506, version 1

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Nicolas Zampieri, Carlos Ramisch, Irina Illina, Dominique Fohr. Identification des Expressions Polylexicales dans les Tweets. RECITAL 2022- Traitement Automatique des Langues Naturelles (TALN), Jun 2022, Avignon, France. ⟨hal-03676506⟩

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