--- title: "Tomás Pinto · University of Lisbon — author profile and papers" description: "Tomás Pinto, University of Lisbon: 2 papers on Elamur Research (2026), h-index 1 — affiliations, topics, co-authors and who cites them in our…" canonical: "https://research.elamur.ai/free/en/authors/tomas-pinto/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/tomas-pinto/) [home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / Tomás Pinto # Tomás Pinto Tomás Pinto has 2 papers in our library, in 2026, most of them on [Information extraction](https://md.research.elamur.ai/free/en/topics/information-extraction/), [Language models & pretraining](https://md.research.elamur.ai/free/en/topics/language-models/), [Evaluation & benchmarks](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/); often with [Catarina Silva](https://md.research.elamur.ai/free/en/authors/catarina-silva/), [Hugo Goncalo Oliveira](https://md.research.elamur.ai/free/en/authors/hugo-goncalo-oliveira/). 2 papers in our library · 2026 [OpenAlex](https://openalex.org/A5133648668) · [ORCID](https://orcid.org/0009-0004-7785-3543) · [**h-index 1**](https://openalex.org/authors/A5133648668) · [6 works](https://openalex.org/works?filter=author.id:A5133648668) · [2 citations](https://openalex.org/works?filter=author.id:A5133648668&sort=cited_by_count:desc) OpenAlex, 2026-10-14 [📄 2 works in our library](https://md.research.elamur.ai/free/en/authors/tomas-pinto/#papers) · [⭐ Paper Stars ranking: #12258](https://md.research.elamur.ai/free/en/paper-stars/page/123/#star-12258) The profile is the library's match of the name; two people with one name are not always told apart. Elsewhere: [Google Scholar](https://scholar.google.com/citations?view_op=search_authors&mauthors=Tom%C3%A1s+Pinto) · [Semantic Scholar](https://www.semanticscholar.org/search?q=Tom%C3%A1s+Pinto) · [dblp](https://dblp.org/search?q=Tom%C3%A1s+Pinto) · [ACL Anthology](https://aclanthology.org/search/?q=Tom%C3%A1s+Pinto) ## Affiliations [🎓**University of Lisbon** Lisbon · Portugal 2023–2026 · 2 papers*current*](https://md.research.elamur.ai/free/en/universities/university-of-lisbon/) · [🎓**University of Coimbra** Coimbra · Portugal 2026 · 1 paper*current*](https://md.research.elamur.ai/free/en/universities/university-of-coimbra/) From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. ## Fields, topics and concepts Of its works in our library, with the number of works on each. 📚 Shelves 6 The field of science this work belongs to (OpenAlex fields).[Artificial Intelligence · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · [Arts and Humanities · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · [Computer Science · 2 works](https://md.research.elamur.ai/free/en/shelves/computer-science/) · [Language and Linguistics · 2 works](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · [Biochemistry, Genetics and Molecular Biology · 1 work](https://md.research.elamur.ai/free/en/shelves/biochemistry-genetics-and-molecular-biology/) · [Molecular Biology · 1 work](https://md.research.elamur.ai/free/en/shelves/biochemistry-genetics-and-molecular-biology/molecular-biology/) 🧭 Topics 3 Research subjects and languages the work is about.[Information extraction · 2 works](https://md.research.elamur.ai/free/en/topics/information-extraction/) · [Evaluation & benchmarks · 1 work](https://md.research.elamur.ai/free/en/topics/evaluation-benchmarks/) · [Language models & pretraining · 1 work](https://md.research.elamur.ai/free/en/topics/language-models/) ## Works by year ### 2020s [**2026** 2 papers](https://md.research.elamur.ai/free/en/authors/tomas-pinto/year/2026/) ## Papers The most cited first (OpenAlex and our library). 1. **[Evaluating Generative Large Language Models for Portuguese Scientific Information Extraction](https://md.research.elamur.ai/free/en/papers/pinto-2026-evaluating-generative-large-language-models/)** *(2026)* Scientific knowledge graphs (SciKGs) depend on reliable extraction of entities and relations from research papers. 2. **[RelEx-PT: A Portuguese Sentence-Level Relation Extraction Dataset](https://md.research.elamur.ai/free/en/papers/pinto-2026-relex-pt-portuguese-sentence-level/)** *(2026)* Portuguese relation extraction lacks clean, controlled benchmarks. Existing resources tend to cover narrow domains, are skewed toward a few relations, target multi-sentence contexts, or depend on costly manual annotation. The authors address this with RelEx-PT, a natively Portuguese dataset in which each sentence has… ## Co-authors here 2 co-authors with a page, the most papers together first. - [Catarina Silva](https://md.research.elamur.ai/free/en/authors/catarina-silva/) ×2 - [Hugo Goncalo Oliveira](https://md.research.elamur.ai/free/en/authors/hugo-goncalo-oliveira/) ×2 ## Venues Where their works here were published, the most works first, with the editions of those that have a page. - [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/): [LREC 2026](https://md.research.elamur.ai/free/en/venues/lrec/2026/) - [Natural Scientific Language Processing (NSLP) @ LREC](https://md.research.elamur.ai/free/en/venues/nslp/): [Natural Scientific Language Processing (NSLP) @ LREC 2026](https://md.research.elamur.ai/free/en/venues/nslp/2026/) Updated 1 November 2026