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VMAWL · 835 P-lemmas · 10 frequency bands · VMC corpus evidence
Generating exercises from the corpus…
New word set every session · All 4 parts of speech · Corpus-grounded feedback
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A corpus-based academic writing assistant for veterinary medicine researchers.
VetLingua is a free AI-powered language tool built on a specialised corpus of published veterinary research articles. It is designed to help researchers explore and understand the linguistic conventions of academic writing in veterinary medicine — not just what to write, but how professionals in the field write.
Unlike general writing assistants, VetLingua is grounded in real corpus data. Every response is informed by the patterns, vocabulary, hedging strategies, reporting verbs, and rhetorical structures found in actual peer-reviewed veterinary research.
The Veterinary Medicine Corpus (VMC) is a machine-generated collection of high-quality, open-access research articles published between 2010 and 2022. Compiled using AntCorGen via the PLOS API, it captures complete articles with structural consistency across five sections: abstract, introduction, materials and methodology, results and discussion, and conclusion.
The VMC comprises 1,449 articles and 7,962,021 tokens, organised into 4 parent categories and 17 child categories with expert guidance to ensure scientifically meaningful classification:
Dr. Mustafa Özer is a researcher and language instructor at the School of Foreign Languages, Abdullah Gül University. His research sits at the intersection of corpus linguistics, English for Specific Purposes (ESP), and academic writing — with a particular focus on the language of veterinary medicine.
VetLingua grew directly out of the corpus Dr. Özer compiled for his PhD thesis — a carefully structured collection of peer-reviewed veterinary research articles spanning 17 topic areas. The compilation methodology and architectural decisions behind this corpus are documented in a peer-reviewed article published in English for Specific Purposes, one of the leading journals in the field.
By making this corpus accessible through an AI-powered conversational interface, Dr. Özer aims to bridge the gap between corpus linguistics research and the practical writing needs of veterinary researchers worldwide.
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