Triple
T22271439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Santeros de Aguada |
E550486
|
entity |
| Predicate | homeCity |
P263
|
FINISHED |
| Object | Aguada |
—
|
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: Aguada | Statement: [Santeros de Aguada, homeCity, Aguada]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aguada Context triple: [Santeros de Aguada, homeCity, Aguada]
-
A.
Aguada
chosen
Aguada is a coastal municipality on Puerto Rico’s west coast known for its beaches and role as a regional commercial and transportation hub.
-
B.
Aguada Cecilio
Aguada Cecilio is a small rural settlement in the Valcheta Department of Río Negro Province in Argentina.
-
C.
Aguadulce
Aguadulce is a coastal town in the province of Almería in southeastern Spain, known for its beaches, marina, and tourism-oriented seafront.
-
D.
Aguadulce
Aguadulce is a city in central Panama known as an agricultural and commercial hub, particularly for sugar and salt production.
-
E.
Aguadas
Aguadas is a historic Colombian town in the Caldas Department, known for its coffee culture, traditional hat-making, and well-preserved colonial architecture.
- 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_69e11e43d8208190aff4f9cf7f2c2a8a |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f141c056cc819088dae6f2b9a1d526 |
completed | April 28, 2026, 11:24 p.m. |
Created at: April 16, 2026, 8:40 p.m.