Triple
T914968
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PlumpJack Winery |
E19746
|
entity |
| Predicate | hasHospitalityComponent |
P22897
|
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: [PlumpJack Winery, hasHospitalityComponent, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHospitalityComponent Context triple: [PlumpJack Winery, hasHospitalityComponent, yes]
-
A.
hasAccommodation
Indicates that an entity provides, owns, or is associated with a place for someone to stay or live.
-
B.
hasResortHotel
Indicates that one entity owns, includes, or is associated with a resort hotel as part of its facilities or offerings.
-
C.
hospitalityContext
Indicates a situational or environmental setting in which hospitality-related interactions, services, or behaviors occur.
-
D.
hasFrontDesk
Indicates that one entity provides or is equipped with a front desk service or reception area for another entity.
-
E.
hasChampagneBar
Indicates that an entity includes, features, or is equipped with a champagne bar.
- 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_69a4939f91a08190ba68c2c81eab90fe |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b6755c488190b7f7848110e3ea2c |
completed | March 1, 2026, 9:58 p.m. |
| PD | Predicate disambiguation | batch_69a4b292d3408190947cbc2f794cf8c5 |
completed | March 1, 2026, 9:41 p.m. |
| PDg | Predicate description generation | batch_69a4b67499708190a65f24d1fd7e4ec5 |
completed | March 1, 2026, 9:58 p.m. |
Created at: March 1, 2026, 7:39 p.m.