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Releases: AuvaLab/itext2kg

iText2KG v0.0.8

29 Jul 10:12
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New Features

  • iText2KG_Star
    • Direct relationship extraction (faster)
    • Eliminates separate entity extraction step
    • No isolated/invented entity handling
  • Dynamic Knowledge Graphs
    • Dynamic KGs with temporal tracking
    • Incremental updates with existing graphs
  • Facts-Based Construction
    • Structured fact extraction via Document Distiller
    • More exhaustive knowledge graphs

Improvements

  • Async Migration: All methods now async/await
  • Enhanced Logging: Structured logging system
  • Universal LangChain Support: All chat/embedding models
  • Better Error Handling: Production-ready reliability

Technical

  • Enhanced relationship extraction
  • Python 3.10+ compatibility
  • Comprehensive examples

We corrected the following issues: #34, #33, #29, #28, #26, #22

Refactoring the iText2KG code

09 Oct 13:45
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-The entire iText2KG code has been refactored by adding data models that describe an Entity, a Relationship, and a Knowledge Graph.

  • Each entity is embedded using both its name and label to avoid merging concepts with similar names but different labels, such as Python: Language and Python: Snake.
  • The weights for entity name embedding and entity label are configurable, with defaults set to 0.4 for the entity label and 0.6 for the entity name.
  • A max_tries parameter has been added to the iText2KG.build_graph function for entity and relation extraction to prevent hallucinatory effects in structuring the output. A max_tries_isolated_entities parameter has been added to the same method to handle hallucinatory effects when processing isolated entities.

Latest update

20 Sep 04:36
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  • Fixing the bug reported in #7.
  • Update the iText2KG build_graph function to perform matching between newly constructed graphs and existing graphs after the construction process.

Supporting other LLMs

17 Sep 09:08
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  • Now, iText2KG is compatible with all the chat/embeddings models LangChain supports. (#1)
    The constructed graph can be expanded by passing the already extracted entities and relationships as arguments to the build_graph function in iText2KG.
  • iText2KG is compatible with all Python versions above 3.9. (#2)
  • Some bugs in the overall architecture are corrected.

Latest update

06 Sep 01:03
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  • Updating the version of neo4j in the requirements.
  • Adding datasets for threshold estimation.
  • Adding the paper link.

Fixing the workflow

16 Jul 11:28
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V0.0.2

Update dependencies in publish_on_pypi.yml and setup.cfg

First Release

16 Jul 11:12
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V0.0.1

Add PyPI publishing workflow and configuration files