Triple
T20643968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santa Ana station |
E507303
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Santa Ana, 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 Ana, California | Statement: [Santa Ana station, locatedIn, Santa Ana, California]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Santa Ana, California Context triple: [Santa Ana station, locatedIn, Santa Ana, California]
-
A.
Santa Ana
chosen
Santa Ana is a major city in Orange County, California, known as a dense urban and governmental center within the Greater Los Angeles metropolitan area.
-
B.
Santa Ana
Santa Ana is a barangay (village-level administrative division) within the highly urbanized city of Taguig in Metro Manila, Philippines.
-
C.
Santa Ana
Santa Ana is a small inhabited island in the Solomon Islands’ Makira-Ulawa Province, known for its traditional culture and coastal village communities.
-
D.
Santa Ana
Santa Ana is a coastal municipality in the province of Cagayan in the Philippines, known for its beaches, marine biodiversity, and the Cagayan Special Economic Zone.
-
E.
Santa Ana
Santa Ana is a major city in western El Salvador known for its colonial architecture, coffee production, and role as an important cultural and economic center.
- 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_69e0b4be702c8190a3d2410a881d310a |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6af1d0be481909e090193dcfd9cf6 |
completed | April 20, 2026, 10:56 p.m. |
Created at: April 16, 2026, 11:43 a.m.