Triple
T16904561
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arseniy Yatsenyuk |
E424525
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Arseniy |
E897562
|
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: Arseniy | Statement: [Arseniy Yatsenyuk, givenName, Arseniy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Arseniy Context triple: [Arseniy Yatsenyuk, givenName, Arseniy]
-
A.
Arseny
chosen
Arseny is a masculine given name of Russian origin, historically borne by several notable figures in literature, art, and public life.
-
B.
Grigory
Grigory is a masculine given name of Russian origin, historically borne by notable figures such as statesman and nobleman Grigory Orlov.
-
C.
Anatoly
Anatoly is a masculine given name of Slavic origin, commonly used in Russian-speaking countries.
-
D.
Zinoviy
Zinoviy is a masculine given name of Slavic origin, commonly used in Russian and Ukrainian contexts.
-
E.
Vasily
Vasily is a masculine given name of Slavic origin, commonly used in Russian-speaking countries.
- 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_69d889da3e8c8190a2b118f383f0beac |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e3c8df454c8190898ebdd75985e51c |
completed | April 18, 2026, 6:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a01413843ec8190b4205aa5fdce28e5 |
completed | May 11, 2026, 2:38 a.m. |
Created at: April 10, 2026, 5:30 a.m.