Triple
T3714251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lynx Air |
E81486
|
entity |
| Predicate | operationalModelFeature |
P29386
|
FINISHED |
| Object | unbundled fares |
—
|
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: unbundled fares | Statement: [Lynx Air, operationalModelFeature, unbundled fares]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: operationalModelFeature Context triple: [Lynx Air, operationalModelFeature, unbundled fares]
-
A.
operatingModel
Indicates how an organization structures and manages its processes, resources, and governance to deliver its products or services.
-
B.
operationalConcept
Indicates that one entity defines, specifies, or embodies the operational concept or way of functioning for another entity.
-
C.
isFeatureOf
chosen
Indicates that something functions as a characteristic, attribute, or component belonging to or describing another entity.
-
D.
facadeFeature
Indicates that one element functions as a distinct architectural or design feature on the façade of another structure.
-
E.
technologicalFeature
Indicates that one entity possesses, exhibits, or is characterized by a specific technological capability, component, or functionality in relation to another 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_69ad8b1a81588190b3f27a5483bb610e |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69adc9ccfad081908730ed15c6f87ce2 |
completed | March 8, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69adc041a8608190a2d543dab6d2ef6c |
completed | March 8, 2026, 6:30 p.m. |
Created at: March 8, 2026, 3:33 p.m.