Triple
T18099518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alexander Godunov |
E433177
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Godunov |
—
|
NE NERFINISHED |
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: Godunov | Statement: [Alexander Godunov, familyName, Godunov]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Godunov Context triple: [Alexander Godunov, familyName, Godunov]
-
A.
Godunov
chosen
Godunov is a Russian surname most famously associated with Boris Godunov, the tsar who ruled Russia at the turn of the 17th century.
-
B.
Matakevich
Matakevich is a surname most notably borne by American football linebacker and special teams standout Tyler Matakevich.
-
C.
Rykov
Rykov is a Russian surname most notably associated with Alexei Rykov, a prominent early Soviet politician and premier.
-
D.
Gus-Khrustalny
Gus-Khrustalny is a town in western Russia known for its historic glass-making industry and status as a local industrial center.
-
E.
Alexander Godunov
Alexander Godunov was a Russian-American ballet dancer and actor best known in film for his memorable villainous role in the action classic "Die Hard."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8b90916008190a1f110bd7ced5473 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4ddb521448190b97d2b2aa7e4d7e6 |
completed | April 19, 2026, 1:50 p.m. |
Created at: April 10, 2026, 10:27 a.m.