Triple
T10053763
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sluzhba vneshney razvedki Rossiyskoy Federatsii |
E208811
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | SVR RF |
E41755
|
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: SVR RF | Statement: [Sluzhba vneshney razvedki Rossiyskoy Federatsii, shortName, SVR RF]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SVR RF Context triple: [Sluzhba vneshney razvedki Rossiyskoy Federatsii, shortName, SVR RF]
-
A.
SVR
SVR is the set of post-nominal letters used to denote recipients of the Order of the White Rose of Finland.
-
B.
SVR
SVR is the ICAO airline designator assigned to Ural Airlines, a Russian commercial air carrier.
-
C.
SVR
chosen
SVR is Russia’s primary foreign intelligence service, which succeeded the Soviet-era KGB’s external intelligence functions after the USSR’s dissolution.
-
D.
libsvm
libsvm is a widely used open-source library that implements Support Vector Machines for classification, regression, and related machine learning tasks.
-
E.
SVC
SVC is the commonly used abbreviation for Sri Venkateswara Creations, a prominent Indian film production company known for producing Telugu-language movies.
- 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_69ca836094408190a36a1ea7e9a86fcd |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cdcf9241208190b38e5e7a1604589c |
completed | April 2, 2026, 2:08 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d282a3d3148190908f02a9588b700e |
completed | April 5, 2026, 3:41 p.m. |
Created at: March 30, 2026, 8:57 p.m.