Deep Learning Brasil at ABSAPT 2022: Portuguese Transformer Ensemble Approaches

Autor:	Gomes, Juliana Resplande Santanna, Garcia, Eduardo Augusto Santos, Junior, Adalberto Ferreira Barbosa, Rodrigues, Ruan Chaves, Silva, Diogo Fernandes Costa, Maia, Dyonnatan Ferreira, da Silva, Nádia Félix Felipe, Filho, Arlindo Rodrigues Galvão, Soares, Anderson da Silva
Rok vydání:	2023
Předmět:	Computer Science - Computation and Language
Druh dokumentu:	Working Paper
Popis:	Aspect-based Sentiment Analysis (ABSA) is a task whose objective is to classify the individual sentiment polarity of all entities, called aspects, in a sentence. The task is composed of two subtasks: Aspect Term Extraction (ATE), identify all aspect terms in a sentence; and Sentiment Orientation Extraction (SOE), given a sentence and its aspect terms, the task is to determine the sentiment polarity of each aspect term (positive, negative or neutral). This article presents we present our participation in Aspect-Based Sentiment Analysis in Portuguese (ABSAPT) 2022 at IberLEF 2022. We submitted the best performing systems, achieving new state-of-the-art results on both subtasks. Comment: 11 pages, 3 figures, In Proceedings of the Iberian Languages Evaluation Forum (IberLEF 2022), Online. CEUR. org
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2311.05051 Zobrazit plný text záznamu View this record from Arxiv