blackBOX25I47/knowledgebase-filtered-sqlite

Knowledgebase Filtered (SQLite)

College-math knowledge graph as a queryable SQLite + FTS5 database, designed for retrieval / tool-call agents (kg_search_statement, kg_get_statement, kg_get_dependencies, md_fetch_section, ...).

What's filtered

The full corpus (887,223 statement nodes) is retained so dependency lookups and full-text search stay complete. Two annotation columns were added to mark the cleaned anchor pool — statements good enough to seed an exam question:

How the 23,182 anchors were selected

• —Base filter: has_proof=1 AND is_closed=1 AND has ≥1 dependency
• —11,750 long anchors (200–4000 chars) — kept directly
• —11,432 short anchors (50–199 chars) — rescued by an LLM completeness check (qwen3.5-35b-a3b, no-think): judged self_contained
• —8,086 short anchors judged incomplete are flagged but not anchor-eligible
• —<50-char statements are excluded from anchoring (too fragmentary)

Usage

import sqlite3
conn = sqlite3.connect("file:index.sqlite?mode=ro&immutable=1", uri=True)
conn.row_factory = sqlite3.Row
# the cleaned anchor pool:
rows = conn.execute("SELECT cid, entity_name FROM statements WHERE anchor_eligible=1").fetchall()

Point the tool layer at it via COLLEGE_MATH_KG_INDEX=/path/to/index.sqlite.

Tables

statements (nodes + the two new columns), fts (FTS5 over name+statement), books (book metadata).