OASYS: Domain-Agnostic Automated System for Constructing Knowledge Base from Unstructured Text

TL;DR

OASYS is a domain-agnostic, automated system for constructing knowledge bases from unstructured text, capable of training without human intervention, specifically designed for Korean language data.

Contribution

It introduces OASYS, the first Korean-language system for automated knowledge base construction that trains solely on auto-generated data, and provides a new benchmark dataset.

Findings

System performs well on Korean benchmark dataset

Generated knowledge base is useful for practical applications

Auto-generated training data effectively supports system training

Abstract

In recent years, creating and managing knowledge bases have become crucial to the retail product and enterprise domains. We present an automatic knowledge base construction system that mines data from documents. This system can generate training data during the training process without human intervention. Therefore, it is domain-agnostic trainable using only the target domain text corpus and a pre-defined knowledge base. This system is called OASYS and is the first system built with the Korean language in mind. In addition, we also have constructed a new human-annotated benchmark dataset of the Korean Wikipedia corpus paired with a Korean DBpedia to aid system evaluation. The system performance results on human-annotated benchmark test dataset are meaningful and show that the generated knowledge base from OASYS trained on only auto-generated data is useful. We provide both a human-annotated test dataset and an auto-generated dataset.