Triple
T23528629
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tapestry Collection by Hilton |
E576500
|
entity |
| Predicate | benefitToGuests |
P66311
|
FINISHED |
| Object | earn and redeem Hilton Honors points |
—
|
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: earn and redeem Hilton Honors points | Statement: [Tapestry Collection by Hilton, benefitToGuests, earn and redeem Hilton Honors points]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: benefitToGuests Context triple: [Tapestry Collection by Hilton, benefitToGuests, earn and redeem Hilton Honors points]
-
A.
benefitsHostBy
Indicates that one entity provides an advantage, improvement, or positive effect to its host entity.
-
B.
benefitsAre
chosen
Indicates that certain advantages, gains, or positive outcomes are possessed by or accrue to a particular entity or group.
-
C.
relationshipWithGuests
Indicates the nature or status of the connection or interaction that someone has with their guests.
-
D.
supportsGuest
Indicates that one entity provides assistance, resources, or accommodation to another entity in the role of a guest.
-
E.
benefits
Indicates that one entity gains an advantage, improvement, or positive outcome as a result of another entity or action.
- 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.