Corpus-Based Approaches to Terminology and Specialized Lexicography

Dear Colleagues,

Artificial Intelligence (AI) and, in particular, Large Language Models (LLMs) are transforming research and practice in terminology, corpus linguistics, and specialised lexicography. Their ability to process vast amounts of textual data, identify domain-specific terminology, generate definitions, model semantic relations, and support multilingual knowledge representation offers new opportunities for the development of specialised lexical resources. At the same time, these technologies raise important questions regarding reliability, transparency, evaluation, linguistic quality, and human expertise in terminology work.

Corpus-based approaches remain fundamental to the systematic analysis of specialised language and the creation of high-quality terminological and lexicographic resources. The integration of AI and LLMs with corpus methodologies has the potential to enhance terminology extraction, terminology management, dictionary compilation, ontology development, and knowledge organisation across specialised domains. However, rigorous empirical research is needed to assess the strengths, limitations, and best practices associated with these emerging technologies.

This Special Issue aims to bring together researchers working at the intersection of AI, corpus linguistics, terminology, and specialised lexicography. We welcome original research articles, review papers, methodological contributions, and case studies that explore innovative corpus-based applications of AI and LLMs for specialised language analysis and resource development.

Topics of interest include, but are not limited to:

* AI-assisted terminology extraction from specialised corpora

* Large Language Models for terminology identification and validation

* Corpus-based approaches to specialised lexicography

* Automatic generation and evaluation of specialised definitions

* Domain adaptation and fine-tuning of LLMs for specialised language

* Multilingual and cross-lingual terminology management

* AI-supported corpus annotation and linguistic analysis

* Terminological knowledge graphs and ontology construction

* Semantic relation extraction from specialised corpora

* AI-assisted dictionary and glossary compilation

* Corpus-based evaluation of AI-generated terminological resources

* Human–AI collaboration in terminology and lexicography

* Explainability and interpretability of AI systems in language resource development

* Bias, ethics, and quality assurance in AI-assisted terminology work

* Applications in medical, legal, technical, environmental, scientific, business, and other specialised domains

* Best practices for integrating corpus linguistics and generative AI in terminology research

We particularly encourage interdisciplinary contributions that combine corpus-driven methodologies with advances in Natural Language Processing, Computational Linguistics, Digital Humanities, Translation Studies, Knowledge Engineering, and Artificial Intelligence.

Authors are invited to submit original manuscripts that have not been published previously and are not under consideration for publication elsewhere. All submissions will undergo MDPI's rigorous single-blind peer-review process and will be evaluated based on scientific quality, originality, methodological soundness, and relevance to the scope of the Special Issue.

We look forward to receiving high-quality contributions that advance our understanding of how AI and corpus-based methodologies can shape the future of terminology and specialised lexicography.

We request that, prior to submitting a manuscript, interested authors initially submit a proposed title and an abstract of 400–600 words summarizing their intended contribution. Please send it to the guest editors (rute.costa@fcsh.unl.pt; mvramos@fcsh.unl.pt; iduran@uco.es) or to Languages editorial office (languages@mdpi.com). Abstracts will be reviewed by the guest editors for the purposes of ensuring proper fit within the scope of the Special Issue. Full manuscripts will undergo double-blind peer-review.

Tentative Completion Schedule
Abstract Submission Deadline: 15 November  2026
Notification of Abstract Acceptance: 15 December 2026
Full Manuscript Deadline: 15 May 2027

Dr. Rute Costa
Dr. Margarida Ramos
Dr. Isabel Durán Muñoz
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a double-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Languages is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

• corpus linguistics
• terminology
• lexicography
• AI
• NLP
• standards
• semantics