Triple
T4635667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steigenberger Hotel Business Bay |
E101522
|
entity |
| Predicate | roomFeature |
P6655
|
FINISHED |
| Object | air conditioning |
—
|
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: air conditioning | Statement: [Steigenberger Hotel Business Bay, roomFeature, air conditioning]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: roomFeature Context triple: [Steigenberger Hotel Business Bay, roomFeature, air conditioning]
-
A.
roofFeature
Indicates that one entity is a feature, element, or characteristic that is part of or associated with a roof.
-
B.
seatFeature
Indicates that a seat possesses or is equipped with a particular feature or characteristic.
-
C.
cabinConfiguration
Indicates how the interior space of a vehicle, vessel, or aircraft is arranged and organized for occupants or cargo.
-
D.
hasTopFloorFeature
Indicates that a building’s top floor possesses a specific feature, attribute, or amenity.
-
E.
hasInteriorFeature
chosen
Indicates that an entity contains or includes a specific feature within its interior space.
- 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_69bd43d2f1c081908cd4b7ec48ecc73d |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd5a60a66c8190b76f3d3a7da1df55 |
completed | March 20, 2026, 2:32 p.m. |
| PD | Predicate disambiguation | batch_69bd5233cb5081908807e2b150f0ca06 |
completed | March 20, 2026, 1:57 p.m. |
Created at: March 20, 2026, 1:13 p.m.