Triple
T19453219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Prodigy (2019 film) |
E486668
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Jeff Buhler |
—
|
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: Jeff Buhler | Statement: [The Prodigy (2019 film), producer, Jeff Buhler]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeff Buhler Context triple: [The Prodigy (2019 film), producer, Jeff Buhler]
-
A.
Jeff Buhler
chosen
Jeff Buhler is an American screenwriter and producer known for his work in horror and science fiction films and television, including adaptations like "Pet Sematary" and series such as "Nightflyers."
-
B.
Scott Huler
Scott Huler is an American author and journalist known for his narrative nonfiction works that often explore science, technology, and culture.
-
C.
Brian Blosil
Brian Blosil is an American record producer and the former husband of entertainer Marie Osmond.
-
D.
Mike Schuler
Mike Schuler is an American basketball coach best known for his successful tenure as head coach of the Portland Trail Blazers in the late 1980s.
-
E.
Todd Boekelheide
Todd Boekelheide is an American film composer and sound editor known for his work on numerous documentaries and feature films, including Academy Award–winning projects.
- 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_69d8e8d86d608190bd199a98d0297f27 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6339407a08190a3e0213bfbb4df3d |
completed | April 20, 2026, 2:09 p.m. |
Created at: April 10, 2026, 1:38 p.m.