Triple
T34394880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suites (Singapore Airlines) |
E882801
|
entity |
| Predicate | cabinAmbienceDesign |
P101123
|
FINISHED |
| Object | luxury hotel room–inspired design |
—
|
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: luxury hotel room–inspired design | Statement: [Suites (Singapore Airlines), cabinAmbienceDesign, luxury hotel room–inspired design]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cabinAmbienceDesign Context triple: [Suites (Singapore Airlines), cabinAmbienceDesign, luxury hotel room–inspired design]
-
A.
cabinComfort
Indicates the degree to which the seating, environment, and amenities within a vehicle’s cabin provide comfort to its occupants.
-
B.
cabinFeatures
chosen
Indicates that a cabin possesses or includes specific features, amenities, or characteristics.
-
C.
cabinConfiguration
Indicates how the interior space of a vehicle, vessel, or aircraft is arranged and organized for occupants or cargo.
-
D.
cabinTypes
Indicates the types or categories of cabins associated with an entity, such as the different classes or configurations available.
-
E.
cabinLocation
Indicates the spatial or geographic location associated with a cabin.
- 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_69f349c1304081909331872829e38106 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f727bde8f88190ad746ca515134ca1 |
completed | May 3, 2026, 10:47 a.m. |
| PD | Predicate disambiguation | batch_69f72739c30c81908642eef3feb3afcf |
completed | May 3, 2026, 10:45 a.m. |
Created at: May 1, 2026, 1:59 a.m.