Triple
T8035332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Virgin America |
E187091
|
entity |
| Predicate | offeredCabinClass |
P3037
|
FINISHED |
| Object | Main Cabin |
—
|
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: Main Cabin | Statement: [Virgin America, offeredCabinClass, Main Cabin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offeredCabinClass Context triple: [Virgin America, offeredCabinClass, Main Cabin]
-
A.
hasCabinClass
chosen
Indicates that an entity (such as a booking, ticket, or seat) is associated with a specific cabin class (e.g., economy, business, first).
-
B.
seatClass
Indicates the travel or seating category assigned to a passenger or seat (e.g., economy, business, first class).
-
C.
hasCabins
Indicates that an entity possesses or includes one or more cabins as part of its structure or facilities.
-
D.
classesOfSeats
Indicates the different categories or types of seats associated with something, such as a venue, vehicle, or event.
-
E.
comfortLevelComparedToPremiumCabins
Indicates how the comfort level of something compares relative to that of premium cabins.
- 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_69ca82ae2d1081909dbfee42b41db419 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3ef68c6081908727d17238b3522a |
completed | March 31, 2026, 3:26 a.m. |
| PD | Predicate disambiguation | batch_69cb049688208190b32088bd2c5930bc |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:22 p.m.