Triple
T21402020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santa Rosa Transit Mall |
E527933
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Santa Rosa, 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 Rosa, California | Statement: [Santa Rosa Transit Mall, locatedIn, Santa Rosa, California]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Santa Rosa, California Context triple: [Santa Rosa Transit Mall, locatedIn, Santa Rosa, California]
-
A.
Santa Rosa
chosen
Santa Rosa is a mid-sized city in Sonoma County known as a cultural and economic hub of California’s wine country.
-
B.
Santa Rosa
Santa Rosa is a rapidly urbanizing city in the Philippine province of Laguna, known as a major industrial, commercial, and residential hub in the Calabarzon region.
-
C.
Santa Rosa
Santa Rosa is a small settlement located on Santa Cruz Island in the Galápagos archipelago of Ecuador.
-
D.
Santa Rosa
Santa Rosa is a residential neighborhood within the municipality of Santa Coloma de Gramenet in the metropolitan area of Barcelona, Spain.
-
E.
Santa Rosa
Santa Rosa is a town that serves as one of the local settlements within the Misiones Department of Paraguay.
- 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_69e0b520ee3c8190abddbee7e37e834c |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e8b1702b44819080b282c22d151c88 |
completed | April 22, 2026, 11:30 a.m. |
Created at: April 16, 2026, 5:18 p.m.