Analysis and Generation of Wikidata Descriptions - Xu, Hutai; Cao, Yuxiang (My University, 2025)
This thesis explores the structure and generation of descriptive texts for Wikidata entities, focusing on cities, universities, and mathematicians. The goal is to develop a grammar-based, language-independent system for automatic description generation. We begin by analyzing multilingual description patterns across six languages, revealing high structural consistency within languages and substantial cross-language variation, particularly between European and non-European language groups. A detailed property frequency analysis shows that a small number of attributes account for the majority of descriptions. Further label occurrence analysis indicates that while human-readable administrative attributes are well represented, identifiers and spatial data are rarely included in natural language descriptions. To mitigate missing label issues, we design a data augmentation pipeline using GeoNames and OpenStreetMap, significantly improving label coverage across languages. We also compare the grammar-based approach with a Retrieval-Augmented Generation (RAG) system and find that the former performs significantly better in terms of clarity, structural consistency, and multilingual alignment. Our findings inform the design of a multilingual description generation system based on Grammatical Framework (GF), emphasizing clarity, informativeness, and structural consistency. This project is part of a broader collaboration: Bokun Xiao contributed to the development of the core grammar, Imtiaz Ayon focused on building the Bengali grammar, and another team was responsible for the Greek grammar.
Keywords: Wikidata; grammatical framework; multilingual description generation