Triple
T17454530
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WZZ |
E424994
|
entity |
| Predicate | associatedAirlineBusinessModel |
P73988
|
FINISHED |
| Object | ultra-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: ultra-low-cost carrier | Statement: [WZZ, associatedAirlineBusinessModel, ultra-low-cost carrier]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedAirlineBusinessModel Context triple: [WZZ, associatedAirlineBusinessModel, ultra-low-cost carrier]
-
A.
associatedAirlineType
chosen
Indicates a relationship where an airline is linked to a specific classification or type (e.g., carrier category or operational class).
-
B.
associatedAirlineServiceType
Indicates the specific type or category of airline service that is linked or related to another entity or activity.
-
C.
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.
-
D.
associatedAirlineGroup
Indicates a relationship where an airline is linked or belongs to a specific airline group or alliance.
-
E.
associatedAirlineFullName
Indicates the full official name of the airline that is associated with a given entity or record.
- 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_69d889db0ba481908402409af3b37917 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4514129f08190ae7581d2915a0373 |
completed | April 19, 2026, 3:51 a.m. |
| PD | Predicate disambiguation | batch_69e3b4f0e3fc819094e466b74622c956 |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:47 a.m.