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3 Repos

Awesome GitHub RepositoriesKnowledge Graph Construction

Assembling large-scale datasets of interconnected entities into graph structures for AI.

Distinct from Large-Scale Dataset Management: Focuses on the assembly and construction of the graph, not just the storage management of the resulting dataset.

Explore 3 awesome GitHub repositories matching data & databases · Knowledge Graph Construction. Refine with filters or upvote what's useful.

Awesome Knowledge Graph Construction GitHub Repositories

Finde die besten Repos mit KI.Wir suchen mit KI nach den am besten passenden Repositories.
  • ownthink/knowledgegraphdataAvatar von ownthink

    ownthink/KnowledgeGraphData

    5,181Auf GitHub ansehen↗

    KnowledgeGraphData is a collection of structured datasets and corpora designed to provide a foundational layer for cognitive intelligence and artificial intelligence systems. It primarily consists of large-scale Chinese knowledge graph datasets, including entity-relation data and NLP training sets used to drive semantic understanding and automated question answering. The project focuses on the construction and export of massive entity-attribute-value graphs, organizing knowledge into portable formats. It provides specialized domain partitioning to tailor information retrieval for professional

    Assembles massive datasets of interconnected entities to create a foundational layer for cognitive artificial intelligence.

    Python
    Auf GitHub ansehen↗5,181
  • spatie/schema-orgAvatar von spatie

    spatie/schema-org

    1,497Auf GitHub ansehen↗

    This library is a PHP tool for programmatically defining, building, and exporting structured data graphs. It provides a fluent, object-oriented interface that allows developers to construct complex, nested metadata structures that comply with standardized vocabulary requirements for search engine indexing. The library distinguishes itself through its support for multi-typed entity modeling, which enables the combination of several classification categories into a single, unified entity. It also features a graph-based modeling system that facilitates the linking and cross-referencing of relate

    Links multiple related entities into a unified collection to represent complex relationships.

    PHPgooglephpschedule
    Auf GitHub ansehen↗1,497
  • yuanxiaosc/entity-relation-extractionAvatar von yuanxiaosc

    yuanxiaosc/Entity-Relation-Extraction

    1,231Auf GitHub ansehen↗

    Entity-Relation-Extraction is a machine learning framework designed to identify entities and their logical connections within unstructured text. It functions as a pipeline that transforms raw documents into structured knowledge graphs by utilizing deep learning models and transformer architectures. The project distinguishes itself through a schema-driven approach, which maps extracted information to predefined relational templates to ensure output consistency. It employs a multi-stage process that combines sequence-labeling token classification with contextual encoding to delineate entity bou

    Populates structured databases by automatically extracting relationships between entities from large volumes of text.

    Pythonbert-modelcompetition-codeentity-extraction
    Auf GitHub ansehen↗1,231
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  2. Data & Databases
  3. Large-Scale Dataset Management
  4. Knowledge Graph Construction

Unter-Tags erkunden

  • Structured Data Graph ConstructionLinks multiple related entities into a unified collection to represent complex relationships. **Distinct from Knowledge Graph Construction:** Distinct from Knowledge Graph Construction: focuses on linking structured data entities for SEO indexing rather than large-scale AI knowledge graph assembly.