Triple
T1099264
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Irina Korina |
E24340
|
entity |
| Predicate | relative |
P37
|
FINISHED |
| Object | Viktor Yelchin |
E21968
|
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: Viktor Yelchin | Statement: [Irina Korina, relative, Viktor Yelchin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Viktor Yelchin Context triple: [Irina Korina, relative, Viktor Yelchin]
-
A.
Viktor Yelchin
chosen
Viktor Yelchin is best known as the father of the late actor Anton Yelchin, who gained fame for his roles in films such as the rebooted Star Trek series.
-
B.
Anton Yelchin
Anton Yelchin was a Russian-American actor best known for playing Pavel Chekov in the rebooted Star Trek film series and for his acclaimed performances in independent movies before his untimely death in 2016.
-
C.
Garrett Hedlund
Garrett Hedlund is an American actor and singer known for roles in films such as "Tron: Legacy," "Friday Night Lights," and "Country Strong."
-
D.
Maxim Peshkov
Maxim Peshkov was the son of the renowned Russian writer Maksim Gorky.
-
E.
Michael Kube-McDowell
Michael Kube-McDowell is an American science fiction author known for his novels, short stories, and contributions to major franchises such as Star Wars.
- 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_69a4940542308190ac2a0b1f730b7cfc |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b9be92688190838ce35cd67e01f3 |
completed | March 1, 2026, 10:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69acce55b5748190b54b8205a735ae89 |
completed | March 8, 2026, 1:18 a.m. |
Created at: March 1, 2026, 7:43 p.m.