Triple
T1543574
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LUV |
E32924
|
entity |
| Predicate | hasUnderlyingCompanyFleetType |
P6198
|
FINISHED |
| Object | all-Boeing 737 fleet |
—
|
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: all-Boeing 737 fleet | Statement: [LUV, hasUnderlyingCompanyFleetType, all-Boeing 737 fleet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUnderlyingCompanyFleetType Context triple: [LUV, hasUnderlyingCompanyFleetType, all-Boeing 737 fleet]
-
A.
hasUnderlyingCompanyBrand
Indicates that one entity is associated with or operates under the corporate brand of another company as its underlying brand.
-
B.
underlyingCompany
Indicates that one entity serves as the fundamental or base company upon which another entity (such as a product, instrument, or structure) is built, derived, or dependent.
-
C.
hasUnderlyingCompanyBusinessModel
Indicates that one entity possesses or is based on a specific company business model that underlies its structure, operations, or value creation.
-
D.
fleetType
chosen
Indicates the category or classification of a fleet to which an entity belongs or with which it is associated.
-
E.
hasUnderlyingCompanyICAOAirlineCode
Indicates that an entity is associated with an underlying company identified by its ICAO airline code.
- 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.