The first-knowledge-graph lesson read the parser output from a key it
never returns (content vs text), then masked the failure with
hard-coded entities, a manually assembled NetworkX graph, and an
uninvoked KGVisualizer; the final cell deleted the sample file, so
rerunning intermediate cells failed. Rework the notebook so every
stage consumes the previous stage's output:
- parse via parsed_document["text"] with an assertion that content
was actually extracted
- real NERExtractor/RelationExtractor output replaces the simulated
entities and wrong hard-coded offsets
- GraphBuilder builds the graph from actual relation endpoints via a
mention-span -> graph-ID map (consistent with notebook 07)
- KGVisualizer.visualize_network renders the graph and saves HTML
- deletion moved to an explicit optional cleanup cell, so parsing and
downstream cells stay rerunnable
Closes#1289
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Seven introduction notebooks linked to a different notebook's filename
in their Colab badge (off-by-one numbering), sending readers to the
wrong notebook or a 404. Point each badge back at its own file.
Add a Cite Us section to the README with BibTeX citation info, and
align it with docs/citation.md (author/organization: Semantica, 2026).
Update LICENSE and docs/project-license.md copyright holder to
Semantica, and replace the stale Hawksight-AI GitHub org slug with
semantica-agi across READMEs, plugin manifests, cookbook notebooks,
and GitHub templates.
taoche