Triple
T17057250
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Margaritaville Island Hotel |
E413855
|
entity |
| Predicate | locatedWithinWalkingDistanceOf |
P61270
|
FINISHED |
| Object | The Island’s shops |
—
|
LITERAL FINISHED |
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: The Island’s shops | Statement: [Margaritaville Island Hotel, locatedWithinWalkingDistanceOf, The Island’s shops]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedWithinWalkingDistanceOf Context triple: [Margaritaville Island Hotel, locatedWithinWalkingDistanceOf, The Island’s shops]
-
A.
nearbyTo
Indicates that one entity is located close in distance or position to another entity.
-
B.
locatedNearPass
Indicates that one entity is situated close to a mountain pass or similar passageway.
-
C.
typicalNearbyLandmarks
Indicates that certain landmarks are commonly found in the vicinity of a given place or location.
-
D.
nearbyLocation
chosen
Indicates that one location is situated close to another location in physical space.
-
E.
proximityToLandmark
Indicates a spatial relationship where one entity is located near or close to a specified landmark.
- 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_69d886cde3d481908d4d01ba88ba7eb7 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3db7a96288190bd985f79c3f55623 |
completed | April 18, 2026, 7:28 p.m. |
| PD | Predicate disambiguation | batch_69e35d60a588819084f53ef9f8b2e7c0 |
completed | April 18, 2026, 10:30 a.m. |
Created at: April 10, 2026, 5:34 a.m.