Triple
T38532963
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Glavny starshina |
E923415
|
entity |
| Predicate | NATOrankApproximation |
P93314
|
FINISHED |
| Object | OR-7 |
—
|
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: OR-7 | Statement: [Glavny starshina, NATOrankApproximation, OR-7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: NATOrankApproximation Context triple: [Glavny starshina, NATOrankApproximation, OR-7]
-
A.
hasApproximateRanking
chosen
Indicates that one entity is assigned a non-exact, estimated, or relative position or order with respect to others.
-
B.
junctionCountApprox
Indicates an approximate count of junctions or connection points involved in or associated with the given entities.
-
C.
hasRandomizedApproximation
Indicates that there exists a randomized algorithm or method that can approximate the result of the referenced entity or process within some probabilistic accuracy or error bounds.
-
D.
rankExample
Indicates that one entity is used as an example or instance to illustrate the rank or ordering of another entity.
-
E.
alignedApproximately
Indicates that two or more entities are positioned or oriented in roughly the same direction or arrangement, allowing for minor deviations or imprecision.
- 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_69f76ea8f6348190a5c03fb6292bbee3 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fcd2e57c088190a2c5cb0b4a93c145 |
completed | May 7, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69fcd1f81cbc8190b4fd3bfc3106c1f3 |
completed | May 7, 2026, 5:55 p.m. |
Created at: May 3, 2026, 4:32 p.m.