Triple
T4602204
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FC Dynamo Kyiv |
E100344
|
entity |
| Predicate | chairman |
P377
|
FINISHED |
| Object | Ihor Surkis |
E466403
|
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: Ihor Surkis | Statement: [FC Dynamo Kyiv, chairman, Ihor Surkis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ihor Surkis Context triple: [FC Dynamo Kyiv, chairman, Ihor Surkis]
-
A.
Ihor Surkis
chosen
Ihor Surkis is a Ukrainian businessman and football executive best known as the long-serving president and influential leader of Dynamo Kyiv.
-
B.
Ivan Levkivskyi
Ivan Levkivskyi is a Python core developer and type system expert known for his contributions to the language’s typing features and pattern matching design.
-
C.
Oleksiy Honcharenko
Oleksiy Honcharenko is a Ukrainian politician and public figure known for his work as a member of parliament and his affiliation with pro-European, reform-oriented political forces.
-
D.
Oleksiy Honcharuk
Oleksiy Honcharuk is a Ukrainian politician and lawyer who served as Prime Minister of Ukraine from 2019 to 2020 under President Volodymyr Zelenskyy.
-
E.
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."
- 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_69bd43cbc014819098b45f435908f88a |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd597462c08190bcdb3efd880778b1 |
completed | March 20, 2026, 2:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be438d66088190b062c8bf4ceba653 |
completed | March 21, 2026, 7:06 a.m. |
Created at: March 20, 2026, 1:11 p.m.