Triple
T2874003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vladimir |
E56831
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Volodymyr |
E210478
|
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: Volodymyr | Statement: [Vladimir, hasVariant, Volodymyr]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Volodymyr Context triple: [Vladimir, hasVariant, Volodymyr]
-
A.
Volodymyr
chosen
Volodymyr is a historic city in western Ukraine known for its medieval heritage and role as a former center of the Volhynia region.
-
B.
Oleksiy
Oleksiy is a common Ukrainian male given name, equivalent to Alexei or Alexey in Russian and Alexius in Latin.
-
C.
Oleksandr
Oleksandr is the Ukrainian form of the given name Alexander, commonly used in Ukraine and among Ukrainian speakers.
-
D.
Yevhen Koshovyi
Yevhen Koshovyi is a Ukrainian comedian and actor best known for his long-time work with the popular comedy troupe and TV show "Kvartal 95."
-
E.
Vladyslav Kryklii
Vladyslav Kryklii is a Ukrainian politician who served as the country’s Minister of Infrastructure in the late 2010s.
- 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_69ab4a4ced288190ab6d3e062d10f7f6 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abe0032ddc8190bb4d15ec7e3c63e8 |
completed | March 7, 2026, 8:21 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b01db780908190919d859205464b2e |
completed | March 10, 2026, 1:33 p.m. |
Created at: March 6, 2026, 10:03 p.m.