Triple
T32722000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | One-Eleven short-haul jet |
E836697
|
entity |
| Predicate | airlineCustomerType |
P15154
|
FINISHED |
| Object | flag carriers |
—
|
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: flag carriers | Statement: [One-Eleven short-haul jet, airlineCustomerType, flag carriers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airlineCustomerType Context triple: [One-Eleven short-haul jet, airlineCustomerType, flag carriers]
-
A.
airlineCustomer
Indicates that one entity is a customer (passenger or client) of an airline entity, typically having purchased or used its air travel services.
-
B.
airlineClass
Indicates the specific travel class or service level assigned to a passenger or ticket on an airline flight.
-
C.
designatedAirlineType
Indicates that an airline has been assigned a specific operational or classification type for a given context or service.
-
D.
airlineType
chosen
Indicates the classification or category of an airline based on its operational or service characteristics.
-
E.
customerType
Indicates the classification or category assigned to a customer based on their characteristics, status, or relationship with a business.
- 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_69f34935455881909088975d79460418 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6c8b3c64881908faa5c22e5785dc8 |
completed | May 3, 2026, 4:01 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f617c08190a70ba880210f908c |
completed | May 3, 2026, 3:41 a.m. |
Created at: May 1, 2026, 1:11 a.m.