Triple
T13614196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fagot |
E325268
|
entity |
| Predicate | aircraftExportedTo |
P5775
|
FINISHED |
| Object | multiple Warsaw Pact countries |
—
|
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: multiple Warsaw Pact countries | Statement: [Fagot, aircraftExportedTo, multiple Warsaw Pact countries]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: aircraftExportedTo Context triple: [Fagot, aircraftExportedTo, multiple Warsaw Pact countries]
-
A.
exportedTo
chosen
Indicates that goods, services, or resources are sent out from one entity or region to another for trade or sale.
-
B.
notableImportedAircraft
Indicates that an entity is notably recognized for having imported a particular aircraft model or type.
-
C.
embarkedAircraft
Indicates that one entity boarded or got onto an aircraft as a passenger or occupant.
-
D.
appliedToAircraftBuiltBy
Indicates that something (such as a regulation, modification, or action) is applied specifically to aircraft that were built by a particular manufacturer or builder.
-
E.
exportedGood
Indicates that a good has been sent out from one country or region to another as part of international trade.
- 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_69d8076aae28819092cf636190ee5529 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbbb9ee3f081909056dc1a92c40b7a |
completed | April 12, 2026, 3:34 p.m. |
| PD | Predicate disambiguation | batch_69dbae1b3ee481909bd43ded6227a3e5 |
completed | April 12, 2026, 2:37 p.m. |
Created at: April 9, 2026, 9:50 p.m.