Natural Language Generation from Wikidata—Architecture, Scalability and Challenges
Journal article, 2026

We present an architecture for generation of Wikipedia articles in several languages from Wikidata. The articles cover the topics of countries, cities, people, universities and professions, and vary in size depending on the amount of available information. The architecture is based on the Grammatical Framework, but we made significant extensions to the framework in order to scale it up to the size of Wikidata. We describe the different scalability issues, and we discuss challenges arising from the current Wikidata structure.

Author

Krasimir Angelov

Undergraduate Education (GRU)

Andrea Carrion del Fresno

Chalmers, Computer Science and Engineering (Chalmers), Functional Programming

Ekaterina Voloshina

Chalmers, Computer Science and Engineering (Chalmers), Functional Programming

Aarne Ranta

Chalmers, Computer Science and Engineering (Chalmers), Computing Science

Computational Linguistics, Information, Reasoning, and AI 2024

1860-949X (ISSN) 1860-9503 (eISSN)

Subject Categories (SSIF 2025)

Natural Language Processing

Computer Sciences

More information

Created

9/15/2026