Triple
T34394870
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Suites (Singapore Airlines) |
E882801
|
entity |
| Predicate | amenityLevelComparedToBusinessClass |
P179158
|
FINISHED |
| Object | higher |
—
|
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: higher | Statement: [Suites (Singapore Airlines), amenityLevelComparedToBusinessClass, higher]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: amenityLevelComparedToBusinessClass Context triple: [Suites (Singapore Airlines), amenityLevelComparedToBusinessClass, higher]
-
A.
comfortLevelRelativeToEconomy
Indicates the degree of comfort or quality relative to a standard economic or budget level.
-
B.
serviceLevelComparedToEconomy
Indicates how the level or quality of service compares relative to an economy (baseline) service level.
-
C.
comfortLevelComparedToPremiumCabins
Indicates how the comfort level of something compares relative to that of premium cabins.
-
D.
baggageAllowanceComparedToPremiumCabins
Indicates how a passenger’s baggage allowance compares in quantity or weight to that granted in premium cabin classes.
-
E.
cabinClassAbove
Indicates that one cabin class is ranked higher or more premium than another in a class hierarchy.
- 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_69f349c1304081909331872829e38106 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f71c35327c8190884f1bfe12bd2cd7 |
completed | May 3, 2026, 9:58 a.m. |
| PD | Predicate disambiguation | batch_69f71822d0e88190ac9731c7ae5a4def |
completed | May 3, 2026, 9:40 a.m. |
| PDg | Predicate description generation | batch_69f71c33edac8190a59f6ff19b265fc5 |
completed | May 3, 2026, 9:58 a.m. |
Created at: May 1, 2026, 1:59 a.m.