Triple
T7837442
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fairmont Hotels and Resorts |
E181720
|
entity |
| Predicate | amenitiesInclude |
P79291
|
FINISHED |
| Object | fine dining restaurants |
—
|
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: fine dining restaurants | Statement: [Fairmont Hotels and Resorts, amenitiesInclude, fine dining restaurants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: amenitiesInclude Context triple: [Fairmont Hotels and Resorts, amenitiesInclude, fine dining restaurants]
-
A.
amenityLevel
Indicates the degree or quality of facilities, services, or conveniences provided in relation to something.
-
B.
hasAmenityAccessTo
Indicates that an entity has the right or ability to use or benefit from a specified amenity or facility.
-
C.
cabinConfiguration
Indicates how the interior space of a vehicle, vessel, or aircraft is arranged and organized for occupants or cargo.
-
D.
hasSpectatorAmenities
Indicates that a place or facility provides amenities or features intended for the comfort or convenience of spectators.
-
E.
accommodationStyle
Indicates the manner or type of lodging or housing arrangement provided or used in a given context.
- 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_69ca8284a25c8190a1a20afad30da792 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb14c203b4819099c039c617628927 |
completed | March 31, 2026, 12:26 a.m. |
| PD | Predicate disambiguation | batch_69cae91e98988190abd4ece75932c589 |
completed | March 30, 2026, 9:20 p.m. |
| PDg | Predicate description generation | batch_69caf7855a3c81908b9318f7186fc0c0 |
completed | March 30, 2026, 10:21 p.m. |
Created at: March 30, 2026, 4:46 p.m.