gBuilder: A Scalable Knowledge Graph Construction System for Unstructured Corpus

Yanzeng Li; Lei Zou

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arXiv · 2208.09705

gBuilder: A Scalable Knowledge Graph Construction System for Unstructured Corpus

Yanzeng Li·Lei Zou

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Abstract

We design a user-friendly and scalable knowledge graph construction (KGC) system for extracting structured knowledge from the unstructured corpus. Different from existing KGC systems, gBuilder provides a flexible and user-defined pipeline to embrace the rapid development of IE models. More built-in template-based or heuristic operators and programmable operators are available for adapting to data from different domains. Furthermore, we also design a cloud-based self-adaptive task scheduling for gBuilder to ensure its scalability on large-scale knowledge graph construction. Experimental evaluation demonstrates the ability of gBuilder to organize multiple information extraction models for knowledge graph construction in a uniform platform, and confirms its high scalability on large-scale KGC tasks.

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Yanzeng Li, Lei Zou. 2022-08-20. gBuilder: A Scalable Knowledge Graph Construction System for Unstructured Corpus. https://arxiv.org/abs/2208.09705

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