Triple
T1858300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SVR |
E41755
|
entity |
| Predicate | abbreviation |
P43
|
FINISHED |
| Object | SVR |
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 | Statement: [SVR, abbreviation, SVR]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: SVR Context triple: [SVR, abbreviation, SVR]
-
A.
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.
-
B.
SVR
SVR is the set of post-nominal letters used to denote recipients of the Order of the White Rose of Finland.
-
C.
SVR
SVR is the ICAO airline designator assigned to Ural Airlines, a Russian commercial air carrier.
-
D.
SVRL
SVRL (Schematron Validation Report Language) is an XML-based reporting format used to express the results of Schematron rule validations.
-
E.
SVC
SVC is scikit-learn’s implementation of a Support Vector Machine classifier used for supervised learning tasks such as binary and multiclass classification.
- 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_69a8864a83848190a4ec02721306c511 |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69abb081405881909e4bea94b9813a4b |
completed | March 7, 2026, 4:58 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69add1ce296c819093336cbaa257dfd2 |
completed | March 8, 2026, 7:45 p.m. |
Created at: March 4, 2026, 7:33 p.m.