Triple
T5056638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ASA |
E113918
|
entity |
| Predicate | airlineTypeAssociatedWith |
P15154
|
FINISHED |
| Object | scheduled passenger airline |
—
|
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: scheduled passenger airline | Statement: [ASA, airlineTypeAssociatedWith, scheduled passenger airline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: airlineTypeAssociatedWith Context triple: [ASA, airlineTypeAssociatedWith, scheduled passenger airline]
-
A.
airlineType
chosen
Indicates the classification or category of an airline based on its operational or service characteristics.
-
B.
airlineAssociatedBrand
Indicates that a brand is commercially or operationally associated with a particular airline, such as through co-branding, partnership, or subsidiary relationships.
-
C.
servesAirlineType
Indicates that a service provider (such as an airport, terminal, or facility) accommodates or operates flights for a specified type or category of airline.
-
D.
airlineBrand
Indicates that one entity functions as the commercial airline brand associated with, or operating under, another entity.
-
E.
airlineCategory
Indicates the classification or type of an airline within a defined categorization system (e.g., full-service, low-cost, regional).
- 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_69bd443aa1f88190abb992d138f2cf42 |
completed | March 20, 2026, 12:57 p.m. |
| NER | Named-entity recognition | batch_69bd744e45588190beaa2f96bb2f41e2 |
completed | March 20, 2026, 4:22 p.m. |
| PD | Predicate disambiguation | batch_69bd715479f08190933604aebd34414f |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:38 p.m.