Triple
T20410381
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Drastic Fantastic |
E500572
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Steve Osborne |
—
|
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: Steve Osborne | Statement: [Drastic Fantastic, producer, Steve Osborne]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Steve Osborne Context triple: [Drastic Fantastic, producer, Steve Osborne]
-
A.
Steve Osborne
chosen
Steve Osborne is a British record producer and mixer known for his work with prominent rock and electronic artists, including remixing tracks for bands like U2.
-
B.
Nick Osborne
Nick Osborne is a film producer best known for his work on the romantic comedy "License to Wed."
-
C.
Alan Balsam
Alan Balsam is a film editor best known for his work on the comedy sequel "Police Academy 4: Citizens on Patrol."
-
D.
Gary Osborne
Gary Osborne is a British songwriter and lyricist best known for his collaborations with artists like Jeff Wayne and Elton John.
-
E.
Jim Osborne
Jim Osborne is the protagonist of the 1952 film noir thriller "The Steel Trap," a bank employee who devises a plan to steal money and flee the country, only to be tormented by guilt and second thoughts.
- 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_69e0b4a935588190b9446a99b37ced44 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67a3ecb348190ae777f6276037828 |
completed | April 20, 2026, 7:10 p.m. |
Created at: April 16, 2026, 11:29 a.m.