Triple
T437871
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andrey Yeremenko |
E10049
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Andrey |
E2779
|
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: Andrey | Statement: [Andrey Yeremenko, givenName, Andrey]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andrey Context triple: [Andrey Yeremenko, givenName, Andrey]
-
A.
Andrei
chosen
Andrei is a masculine given name commonly used in Slavic and Eastern European countries, equivalent to the English name Andrew.
-
B.
Alexey
Alexey is a masculine given name of Slavic origin, commonly used in Russian-speaking countries and derived from the Greek name Alexios, meaning "defender" or "helper."
-
C.
Sergei
Sergei is a masculine given name of Slavic origin, commonly used in Russia and other Eastern European countries.
-
D.
Andrei Voronkov
Andrei Voronkov is a computer scientist known for his influential work in automated reasoning and theorem proving.
-
E.
Andrei Zelentsov
Andrei Zelentsov was a Soviet military commander best known for leading Red Army forces during the Winter War against Finland, including in the Battle of Suomussalmi.
- 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_69a2e8465ef481909655c681b01e2986 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2ef26bb78819089b3b5dac0330619 |
completed | Feb. 28, 2026, 1:35 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a5c38608948190b1fc28a2fec670ea |
completed | March 2, 2026, 5:06 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.