Triple
T35384063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Isla Saona |
E1022733
|
entity |
| Predicate | nearestMajorResortArea |
P139465
|
FINISHED |
| Object | Punta Cana |
—
|
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: Punta Cana | Statement: [Isla Saona, nearestMajorResortArea, Punta Cana]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearestMajorResortArea Context triple: [Isla Saona, nearestMajorResortArea, Punta Cana]
-
A.
nearestMajorRecreationArea
Indicates that one entity is the closest significant recreational area (such as a park, lake, or facility) to another entity in terms of distance.
-
B.
nearbyResortArea
Indicates that a resort area is located close to or within a short distance of a specified place or entity.
-
C.
nearestCityTo
Indicates that one city is the closest in distance to a given location or entity compared to all other cities.
-
D.
nearestArea
Indicates that one area is the closest in distance to a given reference point or region compared to all other candidate areas.
-
E.
nearestMajorArea
chosen
Indicates the relationship where a given location is associated with the closest significant geographic or administrative area.
- F. None of above.
Provenance (3 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_69f76df28d8c819089f2c5799fe7d079 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f79da9f80c8190b0afd8509f28747b |
completed | May 3, 2026, 7:10 p.m. |
| PD | Predicate disambiguation | batch_69f79617d40481909ba372f94209c08b |
completed | May 3, 2026, 6:38 p.m. |
Created at: May 3, 2026, 4:03 p.m.