Triple
T8741711
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SIBERIAN |
E207517
|
entity |
| Predicate | usedByAirlineType |
P15154
|
FINISHED |
| Object | major Russian 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: major Russian airline | Statement: [SIBERIAN, usedByAirlineType, major Russian airline]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedByAirlineType Context triple: [SIBERIAN, usedByAirlineType, major Russian airline]
-
A.
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.
-
B.
airlineType
chosen
Indicates the classification or category of an airline based on its operational or service characteristics.
-
C.
airlinesUse
Indicates that certain airlines operate, employ, or make use of a specified resource, service, or system.
-
D.
designatedAirlineType
Indicates that an airline has been assigned a specific operational or classification type for a given context or service.
-
E.
usedByAircraftType
Indicates that something (such as equipment, infrastructure, or a procedure) is employed or operated by a specific type or category of aircraft.
- 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_69ca835a03a081909d4d4cd01a18c9fb |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5d6fd5dc8190906b7147f27c5d46 |
completed | March 31, 2026, 11:49 p.m. |
| PD | Predicate disambiguation | batch_69cc457322b481908712a9630a17b954 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:38 p.m.