Triple
T11930573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | T-62 |
E283898
|
entity |
| Predicate | producedBy |
P490
|
FINISHED |
| Object | Uralvagonzavod |
E247580
|
NE 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: Uralvagonzavod | Statement: [T-62, producedBy, Uralvagonzavod]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Uralvagonzavod Context triple: [T-62, producedBy, Uralvagonzavod]
-
A.
Uralvagonzavod plant
chosen
The Uralvagonzavod plant is a major Russian industrial complex and one of the world’s largest manufacturers of tanks and railway rolling stock.
-
B.
Uralmash Sverdlovsk
Uralmash Sverdlovsk was the Soviet-era name of the professional football club now known as FC Ural Yekaterinburg, based in Yekaterinburg, Russia.
-
C.
Ural Automotive Plant
Ural Automotive Plant is a Russian manufacturer best known for producing heavy-duty off-road trucks and military vehicles.
-
D.
Izhevsk Mechanical Plant
Izhevsk Mechanical Plant is a major Russian arms manufacturer known for producing a wide range of firearms and military equipment.
-
E.
Volgograd Tractor Plant
Volgograd Tractor Plant is a major industrial enterprise in Volgograd, Russia, historically known for manufacturing tractors and military vehicles, especially during the Soviet era.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6ab2ce9c48190b5d39511b524f666 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d90303a9a88190a4044e6310ba9b4b |
completed | April 10, 2026, 2:02 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f4406ee910819093c72738bfe3f92c |
completed | May 1, 2026, 5:55 a.m. |
Created at: April 8, 2026, 9:45 p.m.