Triple
T16698262
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Well-Groomed Bride |
E405775
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Fred Kohlmar |
—
|
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: Fred Kohlmar | Statement: [The Well-Groomed Bride, producer, Fred Kohlmar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fred Kohlmar Context triple: [The Well-Groomed Bride, producer, Fred Kohlmar]
-
A.
Fred Kohlmar
chosen
Fred Kohlmar was an American film producer active during Hollywood's studio era, known for overseeing a variety of popular comedies and musicals.
-
B.
Edward Knoblauch
Edward Knoblauch, better known as Edward Knoblock, was an American-born British playwright and novelist noted for works such as the play "Kismet."
-
C.
William Diehl
William Diehl was an American novelist best known for his gritty, suspenseful legal and crime thrillers.
-
D.
Paul W. Kiefer
Paul W. Kiefer was an American engineer and industrialist best known for his pioneering role in developing diesel-electric locomotive technology and helping shape modern railroad motive power.
-
E.
Richard M. Schulze
Richard M. Schulze is an American businessman and billionaire best known as the founder and longtime leader of the consumer electronics retail chain Best Buy.
- 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_69d8838db21081909589220fd71440a4 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3832f550c8190bf7514d4611dec6a |
completed | April 18, 2026, 1:12 p.m. |
Created at: April 10, 2026, 5:19 a.m.