Triple
T20596041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kyrgyz Soviet Socialist Republic |
E506050
|
entity |
| Predicate | administrativeCenter |
P1474
|
FINISHED |
| Object | Frunze |
—
|
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: Frunze | Statement: [Kyrgyz Soviet Socialist Republic, administrativeCenter, Frunze]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frunze Context triple: [Kyrgyz Soviet Socialist Republic, administrativeCenter, Frunze]
-
A.
Frunze
chosen
Frunze is a surname most notably associated with Mikhail Frunze, a prominent Bolshevik leader and Red Army commander during the Russian Civil War.
-
B.
Boria
Boria is a deity from ancient Illyrian pagan religion, likely associated with natural forces or local tribal worship.
-
C.
Lyova
Lyova is a Russian diminutive form of the male given name Lev.
-
D.
Yunaska
Yunaska is the maiden surname of Lara Trump, who is married to Eric Trump, son of former U.S. President Donald Trump.
-
E.
Frosta
Frosta is a rural municipality and peninsula in Trøndelag county, Norway, known for its fertile farmland and historical significance as a medieval assembly site.
- 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_69e0b4ba6ae88190af871e1f9522c704 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6aa1bea1c81908b85f38b2a471285 |
completed | April 20, 2026, 10:35 p.m. |
Created at: April 16, 2026, 11:40 a.m.