π Step 1: SQLite Database Partition Manager (projects_kp)
| Project Name | Target Language | AI Model | Total Keywords | Pending | Articles | Actions |
|---|---|---|---|---|---|---|
| Loading project partitions... | ||||||
βοΈ Step 2: Pipeline Configuration & Custom Directive for (proj_kp_person)
π― Step 3: Bulk Keyword & Entity Ingestion Engine
Partition: proj_kp_person
π Current Keywords Queue (proj_kp_person)
| ID | Keyword | Entity Schema | Target Entity | Alias | Status | Queued At | Action |
|---|---|---|---|---|---|---|---|
| Loading keywords... | |||||||
π Step 4: Synthesized KP Articles & Knowledge Graphs
| ID | Title | Category | Target Entity | Schema (@type) | Word Count | Created Date | Action |
|---|---|---|---|---|---|---|---|
| Loading articles... | |||||||
β‘ Step 5: Live KP Daemon Logs (logs_kp/worker.log)
Streaming logs...
π‘ Step 6: Knowledge Panel Indexing Pipeline & Flow Proposal
Conversational user queries like "stevin john leaves blippi" or "boxer named butterbean" or "yamada ryosuke switch" are mapped directly to verified Wikidata/Wikipedia entity graphs through our 4-stage pipeline.
1
Disambiguation Hook Title
Connects general search phrase to primary subject entity in H1 and metadata.
2
Tabular Quick Facts
Injects structured HTML
<table class="quick-facts"> for Knowledge Graph attribute extraction.3
RDF JSON-LD
mentionsIncludes
mentions: [{"@type": "Person", "name": "Stevin John", "sameAs": [...]}] linking Wikidata/IMDb.4
hasPart Section TriplesEmits
hasPart: [{"@type": "WebPageElement", "name": "H2 Heading"}] for section parsing.