RuBQ: A Russian Dataset for Question Answering over Wikidata

Abstract

The paper presents RuBQ, the first Russian knowledge base question answering (KBQA) dataset. The high-quality dataset consists of 1,500 Russian questions of varying complexity, their English machine translations, SPARQL queries to Wikidata, reference answers, as well as a Wikidata sample of triples containing entities with Russian labels. The dataset creation started with a large collection of question-answer pairs from online quizzes. The data underwent automatic filtering, crowd-assisted entity linking, automatic generation of SPARQL queries, and their subsequent in-house verification.

References in corpus (4)

• On the Cross-lingual Transferability of Monolingual Representations
• Large-scale Simple Question Answering with Memory Networks
• Measuring Compositional Generalization: A Comprehensive Method on Realistic Data
• Machine Reading Comprehension: a Literature Review

Cited by in corpus (1)

• QA Dataset Explosion: A Taxonomy of NLP Resources for Question Answering and Reading Comprehension