Triple
T2442071
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andriy |
E53298
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Andrii |
E53298
|
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: Andrii | Statement: [Andriy, hasVariant, Andrii]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Andrii Context triple: [Andriy, hasVariant, Andrii]
-
A.
Andriy
chosen
Andriy is a Slavic given name, equivalent to the English name Andrew.
-
B.
Dmytro
Dmytro is a common Ukrainian male given name, equivalent to "Dmitry" in Russian and derived from the Greek name Demetrios.
-
C.
Oleksiy
Oleksiy is a common Ukrainian male given name, equivalent to Alexei or Alexey in Russian and Alexius in Latin.
-
D.
Oleksandr
Oleksandr is the Ukrainian form of the given name Alexander, commonly used in Ukraine and among Ukrainian speakers.
-
E.
Andriy Zahorodniuk
Andriy Zahorodniuk is a Ukrainian politician and defense expert who served as Ukraine’s Minister of Defence 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_69ab495b6dac8190ac82661aa1452222 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abc9f94e388190b6e49d4f7bbb6697 |
completed | March 7, 2026, 6:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aef0b768f8819084fb74a3a2643cb8 |
completed | March 9, 2026, 4:09 p.m. |
Created at: March 6, 2026, 9:43 p.m.