Triple
T10269578
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | United Economy Plus |
E240799
|
entity |
| Predicate | cabinClassHierarchy |
P93035
|
FINISHED |
| Object | above United Economy |
—
|
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: above United Economy | Statement: [United Economy Plus, cabinClassHierarchy, above United Economy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cabinClassHierarchy Context triple: [United Economy Plus, cabinClassHierarchy, above United Economy]
-
A.
hasCabinClass
Indicates that an entity (such as a booking, ticket, or seat) is associated with a specific cabin class (e.g., economy, business, first).
-
B.
cabinTypes
Indicates the types or categories of cabins associated with an entity, such as the different classes or configurations available.
-
C.
classesOfSeats
Indicates the different categories or types of seats associated with something, such as a venue, vehicle, or event.
-
D.
hotelClass
Indicates the classification or rating level assigned to a hotel, such as its star category or quality tier.
-
E.
areClassifiedBy
Indicates that entities are assigned to one or more categories, types, or classes according to a specified classification scheme.
- 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_69d381a94c1881908fc38fc263d9b9c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4d2872830819080fdfa816167d04c |
completed | April 7, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69d4d1ef6e6c81908a8ee52e4d28127b |
completed | April 7, 2026, 9:44 a.m. |
| PDg | Predicate description generation | batch_69d4d285812c8190ab910dc85c53eebf |
completed | April 7, 2026, 9:46 a.m. |
Created at: April 6, 2026, 11:35 a.m.