Triple
T21130495
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Expedition 14 |
E520670
|
entity |
| Predicate | includedAstronaut |
P122385
|
FINISHED |
| Object | Mikhail Tyurin |
—
|
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: Mikhail Tyurin | Statement: [Expedition 14, includedAstronaut, Mikhail Tyurin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mikhail Tyurin Context triple: [Expedition 14, includedAstronaut, Mikhail Tyurin]
-
A.
Mikhail Tyurin
chosen
Mikhail Tyurin is a Russian cosmonaut and aerospace engineer who has flown multiple long-duration missions to the International Space Station.
-
B.
Boris Tyurin
Boris Tyurin was a mountaineer known for participating in the first successful ascent of the Central Asian peak Khan Tengri.
-
C.
Yuri Nikulin
Yuri Nikulin was a beloved Soviet and Russian clown and film actor, renowned for his work in the Moscow Circus on Tsvetnoy Boulevard and for starring in many classic Soviet comedies.
-
D.
Grigory Yevdokimov
Grigory Yevdokimov was a Soviet political figure and Old Bolshevik who became one of the accused in Stalin’s Great Purge show trials.
-
E.
Yury Vdovin
Yury Vdovin is an architect known for his work on the design of the VDNKh exhibition complex in Moscow.
- 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_69e0b50b53048190ae34e8abbe3c5ada |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e723556ec08190a2ade96c76f9cec7 |
completed | April 21, 2026, 7:12 a.m. |
Created at: April 16, 2026, 2:56 p.m.