Information Extraction (IE), encompassing Named Entity Recognition (NER), Named Entity Linking (NEL), and Relation Extraction (RE), is critical for transforming the rapidly growing volume of scientific publications into structured, actionable knowledge. This need is especially evident in fast-evolving biomedical fields such as the gut-brain axis, where research investigates complex interactions between the gut microbiota and brain-related disorders. Existing biomedical IE benchmarks, however, are often narrow in scope and rely heavily on distantly supervised or automatically generated annotations, limiting their utility for advancing robust IE methods. We introduce GutBrainIE, a benchmark based on more than 1,600 PubMed abstracts, manually annotated by biomedical and terminological experts with fine-grained entities, concept-level links, and relations. While grounded in the gut-brain axis, the benchmark’s rich schema, multiple tasks, and combination of highly curated and weakly supervised data make it broadly applicable to the development and evaluation of biomedical IE systems across domains.

The importance of evaluation in promoting research and development in the information retrieval and natural language processing domains has long been recognised but is this sufficient? In many areas there is still a considerable gap between the results achieved by the research community and their implementation in commercial applications. This is particularly true for the cross-language or multilingual retrieval areas. Despite the strong demand for and interest in multilingual IR functionality, there are still very few operational systems on offer. The Cross Language Evaluation Forum (CLEF) is now taking steps aimed at changing this situation. The paper provides a critical assessment of the main results achieved by CLEF so far and discusses plans now underway to extend its activities in order to have a more direct impact on the application sector.

In this paper we present an evaluation resource for geographic information retrieval developed within the Cross Language Evaluation Forum (CLEF). The GeoCLEF track is dedicated to the evaluation of geographic information retrieval systems. The resource encompasses more than 600,000 documents, 75 topics so far, and more than 100,000 relevance judgments for these topics. Geographic information retrieval requires an evaluation resource which represents realistic information needs and which is geographically challenging. Some experimental results and analysis are reported