Triple
T1543449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Business Select |
E32922
|
entity |
| Predicate | boardingGroupPriority |
P8857
|
FINISHED |
| Object | A1–A15 boarding positions when available |
—
|
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: A1–A15 boarding positions when available | Statement: [Business Select, boardingGroupPriority, A1–A15 boarding positions when available]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: boardingGroupPriority Context triple: [Business Select, boardingGroupPriority, A1–A15 boarding positions when available]
-
A.
boardingGroups
chosen
Indicates that certain entities are assigned to or associated with specific boarding groups for an ordered boarding process.
-
B.
boarding
Indicates that one entity is getting onto or entering a vehicle, vessel, or similar conveyance associated with another entity.
-
C.
boardingProcess
Indicates the process or sequence of actions by which passengers move from a waiting area onto a vehicle (such as an airplane, train, or bus).
-
D.
typeOfPriority
Indicates the specific priority level or category assigned to something relative to other items or tasks.
-
E.
missionPriority
Indicates the relative level of importance or urgency assigned to a mission compared to other missions or tasks.
- 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_69a885ed29088190a3c2d5a3d100c16e |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa95c1a2948190a2b98469afec1a7d |
completed | March 6, 2026, 8:52 a.m. |
| PD | Predicate disambiguation | batch_69a907b2453c8190a41f6b88c8217d1e |
completed | March 5, 2026, 4:33 a.m. |
Created at: March 4, 2026, 7:26 p.m.