Merge remote-tracking branch 'origin/main' into codex/harden-markdown-import-symlinks

This commit is contained in:
Saurabh Meena
2026-08-22 19:38:20 +05:30
17 changed files with 804 additions and 126 deletions
+6 -15
View File
@@ -269,7 +269,7 @@ print("Loaded {} facts from graph".format(count))
## Step 5 — SPARQL queries over enriched working memory
After forward chaining has derived new facts, `SPARQLReasoner` lets you query the enriched working memory using SPARQL triple-pattern matching with optional inference expansion:
After forward chaining has derived new facts, `SPARQLReasoner` prepares SPARQL queries over the enriched working memory with optional inference expansion:
```python
from semantica.reasoning import SPARQLReasoner
@@ -288,22 +288,13 @@ query = """
}
"""
# execute_query() runs: expansion → inference → deduplication
result = sparql.execute_query(query)
for binding in result.bindings:
print("Actor: {:15s} CVE: {}".format(
binding.get("actor", "?"),
binding.get("cve", "?"),
))
# metadata shows how many results came from inference vs ground facts
print("Original: {} Inferred: {}".format(
result.metadata.get("original_count", 0),
result.metadata.get("inferred_count", 0),
))
# expand_query() applies inference rules to the query text:
expanded = sparql.expand_query(query)
print(expanded)
```
`execute_query()` is not implemented yet: no triplet-store execution path exists, so it raises `NotImplementedError` rather than returning an empty result set that callers would misread as "no matches". Until execution lands, run the expanded query against your RDF store directly (for example with `rdflib`).
Inspect the expanded query before running it:
```python