Triple
T20543043
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Soyuz TM-23 |
E504394
|
entity |
| Predicate | crewMember |
P2094
|
FINISHED |
| Object | Yuri Onufrienko |
—
|
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 Onufrienko | Statement: [Soyuz TM-23, crewMember, Yuri Onufrienko]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Yuri Onufrienko Context triple: [Soyuz TM-23, crewMember, Yuri Onufrienko]
-
A.
Yuri Onufrienko
chosen
Yuri Onufrienko is a Russian cosmonaut and former commander of both Mir and International Space Station expeditions.
-
B.
Yury Onufrienko
Yury Onufrienko is a Russian cosmonaut and former military pilot who commanded long-duration missions aboard the International Space Station.
-
C.
Natalya Ivanova
Natalya Ivanova is a film producer known for her work on the movie "Two Women."
-
D.
Natalia Sedova
Natalia Sedova was a Russian revolutionary, Marxist activist, and intellectual best known as the lifelong partner and political collaborator of Leon Trotsky.
-
E.
Susan Ivanova
Susan Ivanova is a strong-willed and tactical Russian-born officer who serves as the second-in-command on the space station Babylon 5 in the science fiction television series of the same name.
- 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_69e0b4b476648190bc6019622ae54d3c |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a293feac8190b27848b64f2db1fe |
completed | April 20, 2026, 10:03 p.m. |
Created at: April 16, 2026, 11:38 a.m.