Triple
T2975065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kaanapali Beach |
E80374
|
entity |
| Predicate | hasNearbyAccommodationType |
P42027
|
FINISHED |
| Object | resorts |
—
|
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: resorts | Statement: [Kaanapali Beach, hasNearbyAccommodationType, resorts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyAccommodationType Context triple: [Kaanapali Beach, hasNearbyAccommodationType, resorts]
-
A.
hasAccommodation
Indicates that an entity provides, owns, or is associated with a place for someone to stay or live.
-
B.
hasAttractionNearby
Indicates that one entity is located close to another entity that serves as an attraction or point of interest.
-
C.
hasReservationNearby
Indicates that an entity has a reservation at a location that is geographically close to a specified reference point or area.
-
D.
nearbyResortArea
chosen
Indicates that a resort area is located close to or within a short distance of a specified place or entity.
-
E.
meetsNear
Indicates that two entities meet or come together at a location that is in close proximity to a specified reference point or 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_69ad8b14ffe881908ffed62f9595c867 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad99894bb0819099fa5cc5166c0eeb |
completed | March 8, 2026, 3:45 p.m. |
| PD | Predicate disambiguation | batch_69ad96105a708190a9ec4838cbcb1207 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:58 p.m.