Triple
T5640948
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rise (song) |
E124263
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Randy Alpert |
E137394
|
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 Alpert | Statement: [Rise (song), producer, Randy Alpert]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Randy Alpert Context triple: [Rise (song), producer, Randy Alpert]
-
A.
Randy Alpert
chosen
Randy Alpert is an American songwriter and producer best known for co-writing the hit song "Hypnotize," famously sampled by The Notorious B.I.G.
-
B.
Michael Ehrlich
Michael Ehrlich is a relatively obscure individual whose primary public mention appears to be as a namesake associated with the surname Ehrlich.
-
C.
Craig Alpert
Craig Alpert is a film editor known for his work on major Hollywood comedies and studio features.
-
D.
John Schulman
John Schulman is an AI researcher and entrepreneur best known as a co-founder of OpenAI and a key contributor to advances in deep reinforcement learning and large language models.
-
E.
Sheldon Lettich
Sheldon Lettich is an American screenwriter and film director best known for his work on action films, including collaborations with Jean-Claude Van Damme and co-writing major Hollywood projects.
- 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_69c00824643c81909ffdb888a2d35189 |
completed | March 22, 2026, 3:17 p.m. |
| NER | Named-entity recognition | batch_69c02286a14481908703ec1741343b76 |
completed | March 22, 2026, 5:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c05a1a14208190a0934d7c6cf0fd5e |
completed | March 22, 2026, 9:07 p.m. |
Created at: March 22, 2026, 3:41 p.m.