Autograph: Factoring Knowledge Graphs into Frames

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Autograph: Factoring Knowledge Graphs into Frames

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Overview

There are many large, generic semantic graphs (e.g. WikiData, DBpedia, etc.) alongside growing numbers of domain-specific ones. LLMs offer a quick path to KG extraction but introduce: Inconsistency: erratic, non-deterministic entity resolution; Inaccuracy: missing or hallucinated predicates; Context loss: unstable frames of reference; Confidence: displaying confidence regardless of accuracy; Speed: impractical at scale. We are developing an AGI-focused KG tooling suite tackling these challenges via four modules—Context Identification, Entity Management, Predicate Management, and Confidence Management. This proposal addresses Context Identification for efficient framing of noisy KGs.

RFP Guidelines

Advanced knowledge graph tooling for AGI systems

Internal Proposal Review
  • Type SingularityNET RFP
  • Total RFP Funding $350,000 USD
  • Proposals 40
  • Awarded Projects n/a
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SingularityNET
Apr. 16, 2025

This RFP seeks the development of advanced tools and techniques for interfacing with, refining, and evaluating knowledge graphs that support reasoning in AGI systems. Projects may target any part of the graph lifecycle — from extraction to refinement to benchmarking — and should optionally support symbolic reasoning within the OpenCog Hyperon framework, including compatibility with the MeTTa language and MORK knowledge graph. Bids are expected to range from $10,000 - $200,000.

Proposal Description

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  • Total Milestones

    3

  • Total Budget

    $60,000 USD

  • Last Updated

    27 May 2025

Milestone 1 - Block Factorization of WikiData Knowledge Graphs

Description

In this milestone we will ingest a JSON dump of WikiData selecting a suitable subset of the properties available and use it to create a test knowledge graph. We will write a production-quality implementation of the block factorization algorithm and test it on the resulting WikiData knowledge graph. We will detail the accuracy and computational efficiency of the decomposition and provide instructions on how to use the software for factorizing large graphs or as a recommender system.

Deliverables

Software for efficient block factorization of large knowledge graphs tooling for ingestion of WikiData and details of the results of factorizing the WikiData knowledge graph.

Budget

$30,000 USD

Success Criterion

Fully operational, general-purpose graph factorization software, with a demonstration on WikiData, and accompanying documentation.

Milestone 2 - Assign Entities & Predicates to Reference Frames

Description

This milestone will probabilistically assign entities and predicates associated with those entities to the frames of reference determined in the first milestone. A specific entity can be assigned to more than one frame of reference - the degree of belonging is constrained to be 1 or less but there is no constraint on the sum of frame of reference assignment values as appropriate. Assignment of entities between more than one frame of reference provides the link between the different elements of the KG. Assignment of entities will be demonstrated on the same WikiData KG used earlier.

Deliverables

Software for entity assignment of factorized knowledge graphs tooling for ingestion of factorized graphs and details of the results of assignment for the WikiData knowledge graph.

Budget

$20,000 USD

Success Criterion

Fully operational, entity assignment software with a demonstration on WikiData and accompanying documentation.

Milestone 3 - Frame of Reference Evaluation and Final Report

Description

The use of factorization into context-driven frames of reference enables more accurately guided and more efficient traversal of large KGs for specific tasks. This we believe introduces a focus mechanism which removes the superfluous information contained in large KGs that will be needed when using AGI-scale KGs for real-world tasks. This milestone will evaluate the quality of this focus.

Deliverables

Detailed report of experimental findings on the factorization and entity assignment of large KGs with efficiency and accuracy assessments determined using WikiData and other KGs as appropriate.

Budget

$10,000 USD

Success Criterion

Delivery of final report.

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