Triple
T20141062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Velvet Buzzsaw |
E491164
|
entity |
| Predicate | musicBy |
P1952
|
FINISHED |
| Object | Buck Sanders |
—
|
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: Buck Sanders | Statement: [Velvet Buzzsaw, musicBy, Buck Sanders]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Buck Sanders Context triple: [Velvet Buzzsaw, musicBy, Buck Sanders]
-
A.
Buck Sanders
chosen
Buck Sanders is an American film composer best known for his Academy Award–nominated work on the war thriller "The Hurt Locker."
-
B.
Frank Clark
Frank Clark was an early 20th-century American film actor known for his roles in silent-era adventure and drama productions.
-
C.
Normie Rowe
Normie Rowe is an Australian pop singer and entertainer who rose to prominence in the 1960s with a string of hit singles and a major teen idol following.
-
D.
Barry Sands
Barry Sands is a sandy beach and coastal area near Carnoustie on the east coast of Scotland, known for its dunes and seaside recreation.
-
E.
Billy Sims
Billy Sims is a former American football running back who won the 1978 Heisman Trophy at the University of Oklahoma and became a Pro Bowl player for the Detroit Lions in the NFL.
- 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_69da6265f8f0819080b29c752a574088 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e6679b179c8190a9511df8ed82098a |
completed | April 20, 2026, 5:51 p.m. |
Created at: April 11, 2026, 11:32 p.m.