Releases: AuvaLab/itext2kg
Releases · AuvaLab/itext2kg
iText2KG v0.0.8
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
-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
- 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
- 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
- Updating the version of neo4j in the requirements.
- Adding datasets for threshold estimation.
- Adding the paper link.
Fixing the workflow
V0.0.2 Update dependencies in publish_on_pypi.yml and setup.cfg
First Release
V0.0.1 Add PyPI publishing workflow and configuration files