Triple
T1543439
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Business Select |
E32922
|
entity |
| Predicate | fareHierarchyLevel |
P14125
|
FINISHED |
| Object | highest fare class on Southwest Airlines |
—
|
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: highest fare class on Southwest Airlines | Statement: [Business Select, fareHierarchyLevel, highest fare class on Southwest Airlines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fareHierarchyLevel Context triple: [Business Select, fareHierarchyLevel, highest fare class on Southwest Airlines]
-
A.
legalHierarchyRank
Indicates the relative position or level of authority an entity holds within a legal or judicial hierarchy.
-
B.
jurisdictionLevel
Indicates the scope or tier of authority under which an entity or action is legally governed or regulated.
-
C.
designationLevel
chosen
Indicates the specific rank, tier, or level assigned to an entity within a designation or classification system.
-
D.
hasDivisionLevel
Indicates that one entity is associated with a specific hierarchical or organizational division level of another entity.
-
E.
amenityLevel
Indicates the degree or quality of facilities, services, or conveniences provided in relation to something.
- 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.