Abstract
This paper presents an overview of the DETESTS-Dis shared task as part of the IberLEF 2024 Workshop on Iberian Languages Evaluation Forum, within the framework of the SEPLN 2024 conference. We proposed two hierarchical subtasks: In subtask 1, participants had to determine the presence of stereotypes in the texts. For subtask 2, participants had to decide which texts labeled with stereotypes were implicit stereotypes. The DETESTS-Dis dataset contains 12,111 comment sentences and tweets in response to newspaper articles and verified racial hoaxes involving immigration in Spanish. 15 teams signed up to participate, 6 of which sent runs, and 3 of them sent their working notes. In this paper, we provide information about the training and test datasets, the systems used by the participants, the evaluation metrics of the systems and their results.
| Original language | English |
|---|---|
| Pages (from-to) | 323-333 |
| Number of pages | 11 |
| Journal | Procesamiento del Lenguaje Natural |
| Volume | 73 |
| DOIs | |
| Publication status | Published - 21 Sept 2024 |
| Event | Iberian Languages Evaluation Forum 2024 - Valladolid, Spain Duration: 24 Sept 2024 → 24 Sept 2024 https://ceur-ws.org/Vol-3756/ |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 10 Reduced Inequalities
Keywords
- Immigration
- Implicitness Detection
- Machine Learning
- Stereotype Detection
ASJC Scopus subject areas
- Language and Linguistics
- Linguistics and Language
- Computer Science Applications
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