Triple
T2874005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vladimir |
E56831
|
entity |
| Predicate | hasVariant |
P455
|
FINISHED |
| Object | Vladimír |
E56831
|
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: Vladimír | Statement: [Vladimir, hasVariant, Vladimír]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vladimír Context triple: [Vladimir, hasVariant, Vladimír]
-
A.
Vladimir
chosen
Vladimir is a common Russian male given name of Slavic origin, historically associated with rulers and notably borne by Russian president Vladimir Putin.
-
B.
Vladimir
Vladimir is a historic Russian city east of Moscow, known as one of the medieval capitals of Russia and a key center of the Golden Ring.
-
C.
Vyacheslav
Vyacheslav is a masculine given name of Slavic origin, most notably borne by Soviet politician Vyacheslav Molotov.
-
D.
Viktor
Viktor is the given name of Viktor Frankl, the Austrian neurologist, psychiatrist, and Holocaust survivor who founded logotherapy and wrote "Man’s Search for Meaning."
-
E.
Viktor
Viktor is a powerful and ancient vampire elder from the "Underworld" film series, portrayed by actor Bill Nighy.
- 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_69b03153b5048190925bfacc07f2db66 |
completed | March 10, 2026, 2:57 p.m. |
Created at: March 6, 2026, 10:03 p.m.