Triple
T23528627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tapestry Collection by Hilton |
E576500
|
entity |
| Predicate | benefitToOwners |
P63508
|
FINISHED |
| Object | Hilton sales and marketing support |
—
|
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: Hilton sales and marketing support | Statement: [Tapestry Collection by Hilton, benefitToOwners, Hilton sales and marketing support]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: benefitToOwners Context triple: [Tapestry Collection by Hilton, benefitToOwners, Hilton sales and marketing support]
-
A.
benefitsAre
Indicates that certain advantages, gains, or positive outcomes are possessed by or accrue to a particular entity or group.
-
B.
benefits
Indicates that one entity gains an advantage, improvement, or positive outcome as a result of another entity or action.
-
C.
benefitsOperator
Indicates that one entity provides an advantage, profit, or positive outcome to an operator entity.
-
D.
benefice
Indicates that one entity grants or bestows a benefit, favor, or advantage upon another.
-
E.
ownerIncentive
chosen
Indicates that an owner has a motivation, benefit, or reward associated with a particular entity, action, or outcome.
- 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_69e245f5a8848190a2ba42e271c6c31f |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1ac758038819098f5f597be39274e |
completed | April 29, 2026, 7 a.m. |
| PD | Predicate disambiguation | batch_69f1189d75b48190a1c01928a993c9fb |
completed | April 28, 2026, 8:29 p.m. |
Created at: April 17, 2026, 6:09 p.m.