Triple
T23523358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tempo by Hilton |
E574565
|
entity |
| Predicate | roomTypeFeature |
P79291
|
FINISHED |
| Object | zones for work and relaxation |
—
|
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: zones for work and relaxation | Statement: [Tempo by Hilton, roomTypeFeature, zones for work and relaxation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roomTypeFeature Context triple: [Tempo by Hilton, roomTypeFeature, zones for work and relaxation]
-
A.
cabinFeatures
Indicates that a cabin possesses or includes specific features, amenities, or characteristics.
-
B.
notableReservationFeature
Indicates that there is a distinctive or noteworthy characteristic associated with a reservation.
-
C.
amenitiesInclude
chosen
Indicates that a place or facility provides or contains specific amenities as part of its features.
-
D.
hasFloorFeature
Indicates that a floor possesses or includes a specific feature or characteristic.
-
E.
cabinConfiguration
Indicates how the interior space of a vehicle, vessel, or aircraft is arranged and organized for occupants or cargo.
- 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_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. |
Created at: April 17, 2026, 6:09 p.m.