Triple
T22863351
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tanya Zhivago |
E566983
|
entity |
| Predicate | relative |
P37
|
FINISHED |
| Object | Yuri Zhivago |
—
|
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: Yuri Zhivago | Statement: [Tanya Zhivago, relative, Yuri Zhivago]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yuri Zhivago Context triple: [Tanya Zhivago, relative, Yuri Zhivago]
-
A.
Yuri Zhivago
chosen
Yuri Zhivago is the idealistic physician and poet whose personal and romantic struggles amid the upheavals of the Russian Revolution form the emotional core of Boris Pasternak’s novel "Doctor Zhivago."
-
B.
Sasha Zhivago
Sasha Zhivago is the son of Yuri Zhivago in Boris Pasternak’s novel "Doctor Zhivago."
-
C.
Tanya Zhivago
Tanya Zhivago is a minor character in Boris Pasternak’s novel "Doctor Zhivago," known primarily as the daughter of the protagonist, Yuri Zhivago.
-
D.
Olesya Rulin
Olesya Rulin is a Russian-American actress best known for her role as Kelsi Nielsen in Disney's "High School Musical" film series.
-
E.
Erast Garin
Erast Garin was a prominent Soviet and Russian actor and theater director known for his distinctive comedic style and roles in classic Soviet cinema.
- 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_69e24589083081908d5694c4fdc80086 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17eff1c18819081dc9dfc1816f746 |
completed | April 29, 2026, 3:46 a.m. |
Created at: April 17, 2026, 3:38 p.m.