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AnnoIndex system enables precise analytical queries over unstructured documents

A new system called AnnoIndex has been developed to improve querying of unstructured documents. It addresses limitations in current retrieval methods by first creating a structured index from text using a process called SchemaLoop, which extracts and organizes information. This structured index allows for precise filtering and querying, with a query engine that compiles questions into SQL extensions. The system prioritizes using the structured index for filtering before resorting to large language models for deep semantic understanding, significantly outperforming existing baselines in experiments. AI

IMPACT Enables more precise and cost-effective information retrieval from unstructured data, potentially improving AI-driven analysis tools.

RANK_REASON The item is an arXiv preprint detailing a new system for document analysis. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.IR (Information Retrieval) →

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AnnoIndex system enables precise analytical queries over unstructured documents

COVERAGE [1]

  1. arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · Nan Tang ·

    Structure then Query: Enabling Precise Analytical Queries over Unstructured Documents

    Unstructured documents constitute the majority of enterprise and web data. With the rapid development of large language models(LLMs), researchers have started to build data systems that analyze unstructured textual documents like operating on databases. However, because mainstrea…