Triple
T1480989
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stanislav Kosior |
E30954
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Stanislav |
E89797
|
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: Stanislav | Statement: [Stanislav Kosior, givenName, Stanislav]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stanislav Context triple: [Stanislav Kosior, givenName, Stanislav]
-
A.
Stanislaw
chosen
Stanislaw is a masculine given name of Slavic origin, most notably borne by the Polish-American mathematician Stanislaw Ulam.
-
B.
Miroslav
Miroslav is a common Slavic male given name, notably borne by Slovak ice hockey star Miroslav Šatan.
-
C.
Pavel
Pavel is a Slavic given name, equivalent to the English name Paul.
-
D.
Leonid
Leonid is a masculine given name of Slavic origin, notably borne by Soviet leader Leonid Brezhnev.
-
E.
Jozef
Jozef is a masculine given name of Hebrew origin, commonly used in Central and Eastern Europe as a variant of Joseph.
- 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_69a498fe55a88190ab7f9e40ace88e49 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c67699848190852e376efe22737c |
completed | March 1, 2026, 11:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ad15b1bea08190a1e21ddc15148d3a |
completed | March 8, 2026, 6:22 a.m. |
Created at: March 1, 2026, 8:11 p.m.