Documentation
This site lets you explore a lightweight knowledge graph derived from automated NER over the corpus.
How to read the site
- Entities are normalized names/terms detected in text (people, places, organizations, etc.).
- Edges connect two entities when they co-occur in the same document.
- Evidence shows the underlying documents and the exact mention spans that produced an edge.
What counts mean
docs counts the number of documents where both entities appear.
pairs is a strength score based on how often both entities are mentioned together within the same document(s).
These are discovery signals; they are not proof of a historical or philosophical relationship.
Database objects (high level)
The site queries a Postgres knowledge-graph schema (typically named kg). The core objects are:
kg.entities: one row per normalized entity (text + label)kg.edges: entity co-mention edges with aggregate countskg.documents: document metadatakg.doc_edges: edge strength broken down by documentkg.mentions: raw mention spans with offsets and labels
Views like kg.vw_top_edges_filtered are used to remove obvious boilerplate and show the most informative edges first.
If you spot a systematic labeling issue (e.g., repeated false positives), it usually means the model or normalization rules should be adjusted and re-run.