Triple
T35403754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Volga-Dnepr Airlines |
E1023307
|
entity |
| Predicate | fleetSpecialization |
P6198
|
FINISHED |
| Object | outsize cargo 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: outsize cargo aircraft | Statement: [Volga-Dnepr Airlines, fleetSpecialization, outsize cargo aircraft]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fleetSpecialization Context triple: [Volga-Dnepr Airlines, fleetSpecialization, outsize cargo aircraft]
-
A.
aircraftRoleSpecialization
Indicates that one aircraft role is a more specific, specialized form of another, more general aircraft role.
-
B.
unitSpecialization
Indicates that one unit is a specialized or more specific version of another unit within a hierarchical or categorical relationship.
-
C.
fleetType
chosen
Indicates the category or classification of a fleet to which an entity belongs or with which it is associated.
-
D.
fleetOrClass
Indicates that something belongs to, is part of, or is categorized under a particular fleet or class.
-
E.
fighterType
Indicates the specific combat or fighting style category that an entity belongs to.
- 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_69f76df43ca4819098711ca4370f1bb9 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7953fa72c8190bd737ef5dfa0ffc0 |
completed | May 3, 2026, 6:34 p.m. |
| PD | Predicate disambiguation | batch_69f7910770108190bdd39ddb5d304f54 |
completed | May 3, 2026, 6:16 p.m. |
Created at: May 3, 2026, 4:03 p.m.