Triple
T13088127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Warsaw Pact airlines |
E310389
|
entity |
| Predicate | typicalFleetSource |
P6198
|
FINISHED |
| Object | Soviet-built aircraft |
—
|
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: Soviet-built aircraft | Statement: [Warsaw Pact airlines, typicalFleetSource, Soviet-built aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalFleetSource Context triple: [Warsaw Pact airlines, typicalFleetSource, Soviet-built aircraft]
-
A.
usesFleetOf
Indicates that one entity operates or relies on a group of vehicles, vessels, or similar assets collectively as a fleet to perform its activities or services.
-
B.
targetFleetType
Indicates the specific category or classification of fleet that is the intended focus or recipient of an action or relationship.
-
C.
fleetIncludes
Indicates that a particular fleet contains or is composed of the specified entity or entities as its members.
-
D.
fleetType
chosen
Indicates the category or classification of a fleet to which an entity belongs or with which it is associated.
-
E.
typicalFuel
Indicates the kind of fuel that is normally or most commonly used by an entity (such as a device, vehicle, or system).
- 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_69d806a733548190989cfd4ce981ca33 |
completed | April 9, 2026, 8:05 p.m. |
| NER | Named-entity recognition | batch_69d981378dd08190b4f00e4e5df0e480 |
completed | April 10, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69d9803f6c508190bfadfbc2d00c2c64 |
completed | April 10, 2026, 10:57 p.m. |
Created at: April 9, 2026, 9:02 p.m.