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Unify: A System For Unstructured Data Analytics

delete2025-08-01
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PRE
AI
J
Jiayi Wang *
Y
Yuan Li
J
Jianming Wu
X
Xu, SH
李国庆 cover
李国庆 (Guoliang Li)
DOI:10.14778/3750601.3750653delete
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Abstract

Abstract

En 中文
Unstructured data comprises over 80% of today's information, yet no specialized system effectively supports its semantic analytics. Traditional SQL-based approaches rely on predefined schemas, making them unsuitable. While large language models (LLMs) enable semantic analysis of unstructured data, manually orchestrating execution plans remains inefficient. This raises a critical question: how can we automate unstructured data analytics? In this demonstration, we present Unify, a system that automates unstructured data analytics for natural language queries. Unify defines a set of core operators for unstructured data processing, with both preprogrammed and LLM-based implementations. It guides LLMs to decompose queries into logical steps and map them to appropriate operators for accurate execution. Our demonstration showcases Unify by real-world scenarios, highlighting its ability to bridge the gap between unstructured data and actionable analytics.

Journal

P
Proceedings of the VLDB Endowment
IF:
3.3
Papers:
556
Citations:
1.2W

Organization

T
Tsinghua University
Scholars:
8.6K
Papers: 4.1K
Citations: 17.7W