Triple
T14600465
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Radio (film) |
E342690
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Herb Gains |
E458818
|
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: Herb Gains | Statement: [Radio (film), producer, Herb Gains]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Herb Gains Context triple: [Radio (film), producer, Herb Gains]
-
A.
Herb Gains
chosen
Herb Gains is a film producer known for his work on the dystopian action movie "The Reaping."
-
B.
Butch Barbella
Butch Barbella is a musician and composer best known for creating the music for the film "A Bronx Tale."
-
C.
Richard Alan Simmons
Richard Alan Simmons was an American screenwriter known for his work in mid-20th-century film and television, including notable science fiction adaptations.
-
D.
Phil Heath
Phil Heath is an American professional bodybuilder renowned for winning multiple consecutive Mr. Olympia titles and being one of the most dominant champions in modern bodybuilding history.
-
E.
Dan Mintz
Dan Mintz is an American comedian, writer, and actor best known for voicing Tina Belcher on the animated television series "Bob's Burgers."
- 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_69d822dec68081908c2553145c4051dc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb438748081908020ce04b869866a |
completed | April 14, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd94cc9fbc819090ae4efe9bc618aa |
completed | May 8, 2026, 7:46 a.m. |
Created at: April 10, 2026, 1:25 a.m.