Overview of ADoBo at IberLEF 2025: Automatic Detection of Anglicisms in Spanish

• Autores: Elena Álvarez Mellado, Jordi Porta Zamorano , Constantine Lignos, Julio Gonzalo Arroyo
• Localización: Procesamiento del lenguaje natural, ISSN 1135-5948, Nº. 75, 2025 (Ejemplar dedicado a: Procesamiento del Lenguaje Natural, Revista nº 75, septiembre de 2025), págs. 373-383
• Idioma: inglés
• Títulos paralelos:
  • Resumen de ADoBo 2025: detección automática de anglicismos en español
• Enlaces
  • Texto completo
• Resumen
  • español

    En este articulo presentamos los resultados de ADoBo 2025, la tarea compartida de IberLEF 2025 sobre detección automática de anglicismos en castellano. La tarea consistió en identificar anglicismos contenidos en una colección de frases en castellano de estilo periodístico. Cinco equipos participaron en la fase de test y propusieron sistemas de diversa naturaleza (LLMs, deep learning, sistemas basados en reglas, sistemas basados en Transformers) con resultados que oscilan entre los 0.17 y los 0.99 puntos de valor F1, lo que ilustra la variabilidad de resultados que distintos sistemas pueden obtener para esta tarea.

  • English

    This paper summarizes the main findings of ADoBo 2025, the shared task on anglicism identification in Spanish proposed in the context of IberLEF 2025. Participants of ADoBo 2025 were asked to detect English lexical borrowings (or anglicisms) from a collection of Spanish journalistic texts. Five teams submitted their solutions for the test phase. Proposed systems included LLMs, deep learning models, Transformer-based models and rule-based systems. The results range from F1 scores of 0.17 to 0.99, which showcases the variability in performance different systems can have for this task.

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