Annotation Framework for Fact Repository Search
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Solution Overview
Problem
Existing information retrieval systems face challenges in efficiently searching and accessing large collections of data from diverse sources, such as the Internet, due to the complexity of storing and organizing information in various formats.
Innovation Solution
A methodology and system for storing annotations of facts in a repository, where each fact is associated with an object, allowing for efficient querying and matching based on attribute-value pairs, with annotations used to determine relevance and eliminate duplicates.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If information is stored in many different formats from diverse sources, then the repository can accommodate diverse data sources, but it becomes difficult to search the data in real-time
Solution Approach 1:
The patent segments information into structured fact entities with standardized attributes (subject, predicate, object) and stores them in a normalized database structure. This segmentation allows diverse source formats to be converted into uniform internal representations, enabling efficient real-time querying while maintaining adaptability to various data sources.
Solution Approach 2:
The patent introduces an intermediary layer consisting of fact extraction modules and normalization processes that mediate between diverse data sources and the search system. This intermediary structure converts unstructured or semi-structured data from various sources into standardized fact entities, resolving the contradiction between format diversity and search efficiency.
2Measurement precision
If annotations are stored for all facts in the repository, then search accuracy and relevance determination improve, but storage requirements and system complexity increase
Solution Approach 1:
The patent applies annotations selectively rather than universally - using entity type annotations, relationship annotations, and confidence score annotations only where needed for accurate search results. This partial annotation approach maintains search precision while avoiding the complexity and storage overhead of annotating every single fact attribute.
Solution Approach 2:
The patent implements local quality by applying different annotation strategies to different fact types and contexts. High-confidence facts receive detailed annotations while low-confidence or straightforward facts use simpler annotation schemes, optimizing the balance between search accuracy and system complexity.
Data Source
AI summary
A fact repository contains facts having attributes and values and further having associated annotations, which are used, among other things, to vet facts in the repository and which can be returned in response to a query.