Triple
T28186884
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ZIPPY |
E716203
|
entity |
| Predicate | associatedWithAirlineBusinessModel |
P73988
|
FINISHED |
| Object | low-cost carrier |
—
|
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: low-cost carrier | Statement: [ZIPPY, associatedWithAirlineBusinessModel, low-cost carrier]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithAirlineBusinessModel Context triple: [ZIPPY, associatedWithAirlineBusinessModel, low-cost carrier]
-
A.
associatedWithAirlineOperations
Indicates a relationship in which an entity is connected to, involved in, or relevant to the operations and activities of an airline.
-
B.
associatedAirlineType
chosen
Indicates a relationship where an airline is linked to a specific classification or type (e.g., carrier category or operational class).
-
C.
associatedAirlineScale
Indicates a relationship where a specific airline is linked to a particular scale, level, or tier used in an aviation-related context (such as pricing, service level, or operational categorization).
-
D.
associatedAirlineServiceType
Indicates the specific type or category of airline service that is linked or related to another entity or activity.
-
E.
associatedAirlineIndustry
Indicates that there is a relationship or connection between an entity and the airline industry, such as involvement, affiliation, or relevance to that sector.
- 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_69efd6b4fc5c81909dd88f01a8c2b35d |
completed | April 27, 2026, 9:35 p.m. |
| NER | Named-entity recognition | batch_6a00ca5e907481909d391afd55938a1b |
completed | May 10, 2026, 6:11 p.m. |
| PD | Predicate disambiguation | batch_6a00ca2214348190a674a85ede709e2e |
completed | May 10, 2026, 6:10 p.m. |
Created at: April 27, 2026, 10:23 p.m.