Triple
T13870921
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MacGyver |
E333446
|
entity |
| Predicate | composer |
P1361
|
FINISHED |
| Object | Randy Edelman |
E359056
|
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: Randy Edelman | Statement: [MacGyver, composer, Randy Edelman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Randy Edelman Context triple: [MacGyver, composer, Randy Edelman]
-
A.
Randy Edelman
chosen
Randy Edelman is an American composer best known for his prolific work on film and television scores, including numerous Hollywood action and drama movies.
-
B.
Don Grusin
Don Grusin is an American jazz and fusion keyboardist, composer, and producer known for his solo work and collaborations within contemporary jazz, including projects with his brother Dave Grusin.
-
C.
Albert Weinert
Albert Weinert was a German-American sculptor and monument designer known for his public memorials in the United States.
-
D.
Dave Grusin
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.
-
E.
Ron Goodwin
Ron Goodwin was a British composer and conductor best known for his rousing film scores for war and adventure movies in the mid-20th century.
- 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_69d81c5ced9c8190b0e9bcc6effe5959 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de05c638248190bbe5d19f7b88d0f9 |
completed | April 14, 2026, 9:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c107c20c81909dff0ca4a59fcc55 |
completed | May 3, 2026, 9:41 p.m. |
Created at: April 9, 2026, 10:14 p.m.