End-to-end example using DatalogReasoner, GraphBuilder, ContextGraph,
GraphAnalyzer, ExplanationGenerator, DatalogFact, and DatalogRule.
Covers ancestor query, KG dependency analysis, RBAC policy, and org hierarchy.
Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com>
- Bug 1: replace dict .get() with dataclass attribute access on
AssociativeClass (name/connects/temporal/properties)
- Bug 2: add full URI to every ontology property and use BASE_URI-prefixed
URIs for all relationship types so TripletStore stores hr:<name>
instead of urn:property:<name>, fixing SPARQL PREFIX hr: queries
- Bug 3: filter None values from EmploymentEvent properties dict so
open-ended employment does not store the literal string "None" as endDate
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- rdf_exporter.py: add isinstance(format, str) guard before .lower() so
non-string inputs (None, int, etc.) raise ValidationError consistently
instead of AttributeError; normalize via strip().lower() in one step
- 15_Export.ipynb: fix notebook cell using result['valid'] → result['overall_valid']
(validate_rdf() returns overall_valid, not valid); add trailing EOF newline
- test_rdf_exporter.py: add tests for non-string format → ValidationError
and for overall_valid key presence in validate_rdf() return value
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Add _format_aliases map in RDFExporter to accept 'ttl', 'nt', 'xml', 'rdf', 'json-ld' as shorthands for canonical format names
- Resolve alias at the start of export_to_rdf() before validation, leaving all existing callers unaffected
- Add TTL alias demo cell to cookbook/introduction/15_Export.ipynb
- Add tests/export/test_rdf_exporter.py covering alias parity, canonical formats, unsupported format error, and file export with format="ttl"
Closes#355
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Add Type import to typing imports in helpers.py to fix retry_on_error decorator
- Remove unused Type import from config_manager.py
- Update capability gap notebook with comment about the fix
- Resolves ImportError when importing semantica modules
Fixes: NameError: name 'Type' is not defined in retry_on_error decorator
- Fixed duplicate setup cells and consolidated into single setup cell
- Resolved undefined variable references in corpus creation
- Moved ontology evaluation to optimal position after semantic extraction
- Enhanced ontology evaluation with extraction context integration
- Removed empty placeholder cells and improved logical flow
- Added semantica package installation requirement
- Updated pipeline sequence to follow correct data processing order
- Improved error handling and variable validation throughout notebook
- Update notebook to use corrected RelationExtractor API
- Move provider/model parameters to initialization
- Add verbose logging for debugging
- Include working relation extraction examples
- Add API key handling in extract_entities_llm(), extract_relations_llm(), and extract_triplets_llm()
- Add explicit api_key handling in NERExtractor and RelationExtractor
- Add llm_model parameter support in extract_triplets_llm() for consistency
- Fix relation extraction bug with type checking for subject_text/object_text
- Add environment variable fallback for API keys
- Update notebook with standard API key pattern
Fixes#147
- Add API key handling in extract_entities_llm(), extract_relations_llm(), and extract_triplets_llm()
- Add llm_model parameter support in extract_triplets_llm() for consistency
- Fix relation extraction bug with type checking for subject_text/object_text
- Add environment variable fallback for API keys
- Include providers.py for context (GroqProvider implementation)
Fixes#145
- Fix import logic in __init__.py to properly export DoclingParser
- Rewrite docling_parser.py to use docling's native API (direct attribute access)
- Remove unsupported features (table_extraction_mode, invalid format_options)
- Use doc.tables, doc.pictures, doc.pages directly instead of dict parsing
- Update notebook with improved code and documentation
- Add proper error handling for when docling is not available
Fixes#138
- Add 8-stage progress tracking (0-100%) with ETA to DoclingParser
- Update earnings call analysis notebook with MDA Space Q3 2025 example
- Simplify notebook code structure
- Add real-time progress visibility for PDF parsing
Closes#133
- Remove top-level torch import from providers.py
- Add lazy imports in HuggingFaceLLMProvider and HuggingFaceModelLoader
- Remove hardcoded API key from notebook
- PyTorch now only loads when HuggingFace providers are instantiated
Fixes#129
- Added DoclingParser class in semantica/parse/ module
- Created earnings call analysis notebook with Docling integration
- Added docling to pyproject.toml as optional dependency
- Maintained backward compatibility with existing parsers
Closes#124
- Deleted cookbook/use_cases/healthcare/02_Drug_Interactions_Analysis.ipynb
- Removed Healthcare section from README.md
- Removed Healthcare section from docs/cookbook.md
- Removed Drug Interactions references from STRATEGIES_SUMMARY.md
- Updated cookbook count from 18 to 17 in all documentation
- Updated docs/index.md to reflect 17 cookbooks
- Add real CSV and JSON data sources for transactions and accounts
- Fix ConflictDetector, TemporalGraphQuery, and Reasoner errors
- Simplify code to use Semantica modules properly
- Enhance GraphRAG section with Context Graph and Groq LLM
- Add temporal interactive visualization using TemporalVisualizer
- Fix CSV export to use CSVExporter instead of GraphExporter
- Update README.md to mention Context Graph and Context Retriever
- Switch entity and relation extraction to ML-based methods (spaCy)
- Fix conflict detection to use detect_temporal_conflicts directly
- Fix graph building to use correct Relation attributes (subject/object/predicate)
- Improve GraphRAG with LLM-based multi-hop reasoning
- Enhance graph analytics output to show all entity types
- Update markdown descriptions with concise bullet points
- Enhanced progress tracker with automatic Jupyter/Colab detection
- Added detailed progress tracking to all deduplication modules
- Added detailed progress tracking to all semantic_extract modules
- Progress tracker now always enabled automatically
- Shows remaining items, percentages, ETA, and processing rates
- Works in both Jupyter notebooks and Google Colab
- Dynamic update intervals based on dataset size
- Improved display handling for Colab compatibility
