Triple
T1684666
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Delta One |
E36414
|
entity |
| Predicate | typicalCabinLayout |
P16894
|
FINISHED |
| Object | 1-2-1 all-aisle-access on many widebody aircraft |
—
|
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: 1-2-1 all-aisle-access on many widebody aircraft | Statement: [Delta One, typicalCabinLayout, 1-2-1 all-aisle-access on many widebody aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalCabinLayout Context triple: [Delta One, typicalCabinLayout, 1-2-1 all-aisle-access on many widebody aircraft]
-
A.
cabinConfiguration
chosen
Indicates how the interior space of a vehicle, vessel, or aircraft is arranged and organized for occupants or cargo.
-
B.
hasCabins
Indicates that an entity possesses or includes one or more cabins as part of its structure or facilities.
-
C.
cabinLocation
Indicates the spatial or geographic location associated with a cabin.
-
D.
numberOfCabins
Indicates the total count of cabins associated with a given entity.
-
E.
chamberType
Indicates the specific kind or category of chamber associated with an entity (e.g., room, compartment, or enclosed space type).
- 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_69a886151508819084fa7f1ce6e05577 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aba644070c81908745b56d981fe273 |
completed | March 7, 2026, 4:15 a.m. |
| PD | Predicate disambiguation | batch_69aa61b57a6881909373af287ef24799 |
completed | March 6, 2026, 5:10 a.m. |
Created at: March 4, 2026, 7:29 p.m.