Triple
T22708624
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | STS9 |
E561529
|
entity |
| Predicate | basedIn |
P40
|
FINISHED |
| Object | Santa Cruz, California |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Santa Cruz, California | Statement: [STS9, basedIn, Santa Cruz, California]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Santa Cruz, California Context triple: [STS9, basedIn, Santa Cruz, California]
-
A.
Santa Cruz, California
chosen
Santa Cruz, California is a coastal city in Northern California known for its surf culture, beach boardwalk, and progressive university community.
-
B.
Santa Cruz
Santa Cruz is a notable wine-producing city in central Chile’s Colchagua Valley, recognized for its vineyards, tourism, and colonial charm.
-
C.
Santa Cruz
Santa Cruz is a coastal municipality in the Philippine island province of Marinduque known for its fishing communities and rural island-barangays.
-
D.
Santa Cruz
Santa Cruz is a Christian religious dedication to the Holy Cross, venerated as the patron of the Spanish municipality of Abanilla.
-
E.
Santa Cruz
Santa Cruz is a coastal municipality in the province of Occidental Mindoro in the Philippines, known for its agricultural communities and access to marine resources.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69e2454f1348819088d83f420925a5c1 |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f178d11d4081909981872698b6c45e |
completed | April 29, 2026, 3:19 a.m. |
Created at: April 17, 2026, 3:17 p.m.