Triple
T23523355
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tempo by Hilton |
E574565
|
entity |
| Predicate | experienceEmphasis |
P153091
|
FINISHED |
| Object | well-being |
—
|
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: well-being | Statement: [Tempo by Hilton, experienceEmphasis, well-being]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: experienceEmphasis Context triple: [Tempo by Hilton, experienceEmphasis, well-being]
-
A.
experienceType
Indicates the specific kind or category of experience associated with an entity or event.
-
B.
experienceIncludes
Indicates that a particular experience encompasses, contains, or involves a specified component, activity, or element as part of it.
-
C.
recommendedExperience
Indicates that a certain level or type of prior experience is advised or preferred for engaging in the related activity, role, or item.
-
D.
primaryExperience
Indicates that one entity is the main or most significant experience associated with another entity, as opposed to secondary or supporting experiences.
-
E.
usedExperienceIn
Indicates that an entity applied or leveraged a particular experience or expertise in performing an action or achieving a result.
- 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_69e245bb3dcc8190ba9a2b35972b58d0 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1ac71ec8881909bfb706efdc2518f |
completed | April 29, 2026, 7 a.m. |
| PD | Predicate disambiguation | batch_69f1189d75b48190a1c01928a993c9fb |
completed | April 28, 2026, 8:29 p.m. |
| PDg | Predicate description generation | batch_69f12760784c8190aaeff002ef31febe |
completed | April 28, 2026, 9:32 p.m. |
Created at: April 17, 2026, 6:09 p.m.