Triple
T1543415
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wanna Get Away |
E32921
|
entity |
| Predicate | seatAssignmentPolicy |
P9552
|
FINISHED |
| Object | no assigned seats (open seating on Southwest) |
—
|
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: no assigned seats (open seating on Southwest) | Statement: [Wanna Get Away, seatAssignmentPolicy, no assigned seats (open seating on Southwest)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seatAssignmentPolicy Context triple: [Wanna Get Away, seatAssignmentPolicy, no assigned seats (open seating on Southwest)]
-
A.
seatSelectionPolicy
chosen
Indicates the rules or constraints governing how seats are chosen or assigned in a given context.
-
B.
seatNotationSystem
Indicates the system or convention used to label, number, or otherwise denote seats within a venue or vehicle.
-
C.
reservationPolicy
Indicates the rules or conditions governing how reservations are made, modified, or canceled between parties.
-
D.
seatingConfiguration
Indicates how seats are arranged or organized relative to each other in a given context.
-
E.
seatCategory
Indicates the classification or type of a seat (e.g., by comfort level, price tier, or section) assigned to an entity.
- 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.