The aim of this exploratory study is to test the possibility of enhancing the quality of institutional communication related to diabetes self-treatment by switching from manual to prompt-based writing. The study proposes an investigation into the use of prompts applied to controlled natural language, particularly in Italian, French and English. Starting from a corpus of three comparable texts concerning the so-called Rule of 15, a reformulation is undertaken in accordance with the principles of controlled natural languages. Feedback will be gathered through a Likert scale questionnaire and a comprehension test administered to anonymous volunteers.

The integration of artificial intelligence (AI) with terminology management (TM) has opened new avenues for enhancing efficiency and precision in both fields, necessitating standardized approaches to ensure interoperability and ethical application. The newly formed ISO/TC 37/SC 3/WG 6 represents the first dedicated initiative to study the standardization of the mutual improvements of AI and TM. This group aims to develop standardized frameworks and guidelines that optimize the interaction between AI technologies and terminology resources, benefiting professionals, systems, and practices in both domains. This article presents the state-of-the-art in the mutual relationship between AI and TM, highlighting opportunities for bidirectional advancements. It also addresses limitations and challenges from a standardization perspective. By tackling these issues, ISO/TC 37/SC 3/WG 6 seeks to establish principles that ensure scalability, precision, and ethical considerations, shaping future standards to support global communication and knowledge exchange.

We present the results of the ninth edition of the Biomedical Translation Task at WMT’24. We released test sets for six language pairs, namely, French, German, Italian, Portuguese, Russian, and Spanish, from and into English. Eachtest set consists of 50 abstracts from PubMed. Differently from previous years, we did not split abstracts into sentences. We received submissions from five teams, and for almost all language directions. We used a baseline/comparison system based on Llama 3.1 and share the source code at https://github.com/cgrozea/wmt24biomed-ref.

We present an overview of the Biomedical Translation Task that was part of the Eighth Conference on Machine Translation (WMT23). The aim of the task was the automatic translation of biomedical abstracts from the PubMed database. It included twelve language directions, namely, French, Spanish, Portuguese, Italian, German, and Russian, from and into English. We received submissions from 18 systems and for all the test sets that we released. Our comparison system was based on ChatGPT 3.5 and performed very well in comparison to many of the submissions.

In this paper, we propose the description of a very recent interdisciplinary project aiming at analysing both the conceptual and linguistic dimensions of humanitarian rights terminology. This analysis will result in the form of a new knowledge-based multilingual terminological resource which is designed in order to meet the FAIR principles for Open Science and will serve, in the future, as a prototype for the development of a new software for the simplified rewriting of international legal texts relating to human rights. Given the early stage of the project, we will focus on the description of its rationale, the planned workflow, and the theoretical approach which will be adopted to achieve the main goal of this ambitious research project.

In the seventh edition of the WMT Biomedical Task, we addressed a total of seven languagepairs, namely English/German, English/French, English/Spanish, English/Portuguese, English/Chinese, English/Russian, English/Italian. This year’s test sets covered three types of biomedical text genre. In addition to scientific abstracts and terminology items used in previous editions, we released test sets of clinical cases. The evaluation of clinical cases translations were given special attention by involving clinicians in the preparation of reference translations and manual evaluation. For the main MEDLINE test sets, we received a total of 609 submissions from 37 teams. For the ClinSpEn sub-task, we had the participation of five teams.

In the sixth edition of the WMT Biomedical Task, we addressed a total of eight language pairs, namely English/German, English/French, English/Spanish, English/Portuguese, English/Chinese, English/Russian, English/Italian, and English/Basque. Further, our tests were composed of three types of textual test sets. New to this year, we released a test set of summaries of animal experiments, in addition to the test sets of scientific abstracts and terminologies. We received a total of 107 submissions from 15 teams from 6 countries.

The process of standardization plays an important role in the management of terminological resources. In this context, we present the work of re-modeling an existing multilingual terminological database for the medical domain, named TriMED. This resource was conceived in order to tackle some problems related to the complexity of medical terminology and to respond to different users’ needs. We provide a methodology that should be followed in order to make a termbase compliant to the three most recent ISO/TC 37 standards. In particular, we focus on the definition of i) the structural meta-model of the resource, ii) the data categories provided, and iii) the TBX format for its implementation. In addition to the formal standardization of the resource, we describe the realization of a new data category repository for the management of the TriMED terminological data and a Web application that can be used to access the multilingual terminological records.

Machine translation of scientific abstracts and terminologies has the potential to support health professionals and biomedical researchers in some of their activities. In the fifth edition of the WMT Biomedical Task, we addressed a total of eight language pairs. Five language pairs were previously addressed in past editions of the shared task, namely, English/German, English/French, English/Spanish, English/Portuguese, and English/Chinese. Three additional languages pairs were also introduced this year: English/Russian, English/Italian, and English/Basque. The task addressed the evaluation of both scientific abstracts (all language pairs) and terminologies (English/Basque only). We received submissions from a total of 20 teams. For recurring language pairs, we observed an improvement in the translations in terms of automatic scores and qualitative evaluations, compared to previous years.