Abstract

Abstract

Abstract
Over the last three years, the JOKER Lab series at CLEF has gathered an active community of researchers in natural language processing and information retrieval to collaborate on non-literal use of language in text. Such language can be a challenge for AI systems, but also sometimes for humans, as it requires understanding implicit cultural references and unorthodox interactions between form and meaning. In this paper, we discuss the lessons learned from the previous iterations of the Lab and describe how its upcoming edition will build upon those to address new challenges. In 2025, JOKER will provide novel tasks and update some previous ones with new data and new languages. This year we provide sandbox environments for experimenting with humour-aware information retrieval (Task 1), a previously featured task now enhanced with an all-new Portuguese corpus; wordplay translation in text (Task 2), another historical task for which we provide new corpora; onomastic wordplay (Task 3), a new task focussed on humorous proper names in fiction; and controlled creativity (Task 4), another novel task that aims at identifying and avoiding hallucinations. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

Abstract
Around 80% of websites change significantly or disappear altogether after the first year, resulting in the loss of invaluable information. In this volatile scenario, preserving online content is increasingly essential. This is especially critical for local news outlets, which produce a wealth of information within the unique context of their communities but often lack sufficient archiving resources. In this paper, we take a significant step forward by leveraging the information preserved by the Portuguese Web Archive, Arquivo.pt, to recreate the website of a local news outlet. This online demo grants users direct access to previously lost news articles, images, and front covers, thus contributing to preserving local digital heritage. An IR system was also implemented to ensure easy access, along with a recommendation system based on BERT embeddings to suggest related news articles and enhance user engagement. As a final contribution, we also provide a Python package, enabling others to replicate the process of collecting, processing, retrieving, and recreating websites for local news outlets in Portugal. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.