Triple
T6966573
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dave Grusin |
E161503
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Dave Grusin |
E161503
|
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: Dave Grusin | Statement: [Dave Grusin, name, Dave Grusin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dave Grusin Context triple: [Dave Grusin, name, Dave Grusin]
-
A.
Dave Grusin
chosen
Dave Grusin is an American composer, arranger, and jazz pianist best known for his prolific film and television scores and for co-founding GRP Records.
-
B.
Randy Edelman
Randy Edelman is an American composer best known for his prolific work on film and television scores, including numerous Hollywood action and drama movies.
-
C.
Lalo Schifrin
Lalo Schifrin is an Argentine-American composer, pianist, and conductor best known for his iconic film and television scores, including the theme for "Mission: Impossible."
-
D.
Albert Weinert
Albert Weinert was a German-American sculptor and monument designer known for his public memorials in the United States.
-
E.
Michael Franks
Michael Franks is an American jazz and soft rock singer-songwriter known for his smooth vocal style and sophisticated, often witty lyrics.
- 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_69c68853cff881908439d488924a8283 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6db121174819098e73e45f6c9cc91 |
completed | March 27, 2026, 7:31 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c758a57b8481908cef7de9b3abf7a3 |
completed | March 28, 2026, 4:27 a.m. |
Created at: March 27, 2026, 2:30 p.m.