Triple
T23265773
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RSDLP(b) |
E588141
|
entity |
| Predicate | activeIn |
P1560
|
FINISHED |
| Object | Soviet Russia |
—
|
NE NERFINISHED |
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: Soviet Russia | Statement: [RSDLP(b), activeIn, Soviet Russia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Soviet Russia Context triple: [RSDLP(b), activeIn, Soviet Russia]
-
A.
Soviet Union
The Soviet Union was a socialist superpower that dominated Eastern Europe and led the communist bloc during the Cold War.
-
B.
Rusguniae
Rusguniae was an important ancient coastal city in the Roman province of Mauretania Caesariensis, located in what is now northern Algeria.
-
C.
АН СССР
АН СССР was the highest scientific institution of the Soviet Union, overseeing and coordinating research across a wide range of scientific disciplines.
-
D.
Russian SFSR
chosen
The Russian SFSR was the largest and most influential republic of the former Soviet Union, encompassing much of its political, economic, and cultural center.
-
E.
Rusko
Rusko is a small municipality in southwestern Finland known for its rural character and proximity to the city of Turku.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e25d148adc819088efbf42672604e9 |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f194cc3b908190aaefd036aa2b52b5 |
completed | April 29, 2026, 5:19 a.m. |
Created at: April 17, 2026, 4:35 p.m.