Litcius/Paper detail

GenWiki: A Dataset of 1.3 Million Content-Sharing Text and Graphs for Unsupervised Graph-to-Text Generation

Zhijing Jin, Qipeng Guo, Xipeng Qiu, Zheng Zhang

202027 citationsDOIOpen Access PDF

Abstract

Data collection for the knowledge graph-to-text generation is expensive. As a result, research on unsupervised models has emerged as an active field recently. However, most unsupervised models have to use non-parallel versions of existing small supervised datasets, which largely constrain their potential. In this paper, we propose a large-scale, general-domain dataset, GenWiki. Our unsupervised dataset has 1.3M text and graph examples, respectively. With a human-annotated test set, we provide this new benchmark dataset for future research on unsupervised text generation from knowledge graphs.

Topics & Concepts

Computer scienceKnowledge graphBenchmark (surveying)GraphArtificial intelligenceSet (abstract data type)Field (mathematics)Unsupervised learningMachine learningNatural language processingTheoretical computer scienceMathematicsGeographyPure mathematicsProgramming languageGeodesyTopic ModelingNatural Language Processing TechniquesMultimodal Machine Learning Applications