Triple
T27282581
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Playa de las Vistas |
E688378
|
entity |
| Predicate | hasResortHotelsNearby |
P197550
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Playa de las Vistas, hasResortHotelsNearby, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasResortHotelsNearby Context triple: [Playa de las Vistas, hasResortHotelsNearby, yes]
-
A.
hasNearbyHotel
Indicates that one entity is located close to or within a short distance of a hotel.
-
B.
hasAirportHotelNearby
Indicates that an airport has at least one hotel located in its immediate vicinity or within a short travel distance.
-
C.
hasResortHotel
Indicates that one entity owns, includes, or is associated with a resort hotel as part of its facilities or offerings.
-
D.
hasNearbyHotelCluster
Indicates that one or more hotels are located in close proximity to the referenced place or area, forming a spatial cluster.
-
E.
hasNearbyLodge
Indicates that one entity is located close to or in the vicinity of a lodge associated with another entity.
- F. None of above. chosen
Provenance (4 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_69ef355998e08190bdff849e8f33adce |
completed | April 27, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69fe9b0276d48190b554fa22b043e6d8 |
completed | May 9, 2026, 2:25 a.m. |
| PD | Predicate disambiguation | batch_69fe999692b081909921e1148d66f0ef |
completed | May 9, 2026, 2:19 a.m. |
| PDg | Predicate description generation | batch_69fe9b013ec481908f89beddb9c4cd4e |
completed | May 9, 2026, 2:25 a.m. |
Created at: April 27, 2026, 11:08 a.m.