Triple
T13752297
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Embraer 175 |
E330382
|
entity |
| Predicate | cabinClassOptions |
P85721
|
FINISHED |
| Object | single-class |
—
|
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: single-class | Statement: [Embraer 175, cabinClassOptions, single-class]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cabinClassOptions Context triple: [Embraer 175, cabinClassOptions, single-class]
-
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.
cabinClassAbove
Indicates that one cabin class is ranked higher or more premium than another in a class hierarchy.
-
C.
cabinTypes
chosen
Indicates the types or categories of cabins associated with an entity, such as the different classes or configurations available.
-
D.
seatClass
Indicates the travel or seating category assigned to a passenger or seat (e.g., economy, business, first class).
-
E.
cabinClassBelow
Indicates that one entity’s cabin class is ranked lower or less premium than another entity’s cabin class.
- 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_69d81c573f288190aa2403d484fa3d49 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de0215cfa08190aaed8b089aff217b |
completed | April 14, 2026, 9 a.m. |
| PD | Predicate disambiguation | batch_69dbbe950b148190ba0df8a749269ec6 |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 10:09 p.m.