Triple
T20850768
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | El Zagal |
E513353
|
entity |
| Predicate | region |
P40
|
FINISHED |
| Object | Granada |
—
|
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: Granada | Statement: [El Zagal, region, Granada]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Granada Context triple: [El Zagal, region, Granada]
-
A.
Granada
chosen
Granada is a historic city in southern Spain, renowned as the last stronghold of Muslim rule on the Iberian Peninsula and home to the famed Alhambra palace.
-
B.
Granada
Granada is a municipality in the Cundinamarca Department of central Colombia, known for its agricultural economy and proximity to the Bogotá metropolitan area.
-
C.
Granada
Granada is a small rural town in southeastern Colorado, historically known as the site of the World War II-era Amache Japanese American internment camp.
-
D.
Granada
Granada is a historic colonial city in western Nicaragua, known for its well-preserved Spanish architecture and location on the shores of Lake Nicaragua.
-
E.
Granada
Granada is a Colombian town and municipality in the Meta Department, known for its agricultural economy and role as a regional service center in the Llanos Orientales.
- 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_69e0b4f4898081908209e58edb8f9c45 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c352ca8c819094545dbe67bfe3dc |
completed | April 21, 2026, 12:22 a.m. |
Created at: April 16, 2026, 12:43 p.m.