Triple
T18289250
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | King Kong (2005 film) |
E438064
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Jan Blenkin |
—
|
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: Jan Blenkin | Statement: [King Kong (2005 film), producer, Jan Blenkin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jan Blenkin Context triple: [King Kong (2005 film), producer, Jan Blenkin]
-
A.
Jan Blenkin
chosen
Jan Blenkin is a film producer best known for his work on major Hollywood productions such as Peter Jackson’s 2005 remake of King Kong.
-
B.
Jan Kleyna
Jan Kleyna is an astronomer known for discovering small outer moons of Jupiter and contributing to the study of planetary satellites.
-
C.
Joost de Blank
Joost de Blank was a 20th-century Anglican clergyman known for his outspoken opposition to apartheid while serving as Archbishop of Cape Town.
-
D.
Peter Wildoer
Peter Wildoer is a Swedish drummer known for his technical, high-speed playing in metal bands such as Darkane and for his work as a session and touring musician.
-
E.
Leo Beenhakker
Leo Beenhakker is a Dutch football manager renowned for coaching top clubs and national teams, including Real Madrid, Ajax, and the Netherlands.
- 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_69d8b914530c8190b4474d862a2b2a1b |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e500fd65888190afdbb29dc60066af |
completed | April 19, 2026, 4:21 p.m. |
Created at: April 10, 2026, 10:35 a.m.