Triple
T6380564
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Smooth |
E143568
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Matt Serletic |
E470738
|
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: Matt Serletic | Statement: [Smooth, producer, Matt Serletic]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Matt Serletic Context triple: [Smooth, producer, Matt Serletic]
-
A.
Matt Serletic
chosen
Matt Serletic is an American record producer and music executive best known for his work with artists like Matchbox Twenty, Santana, and Aerosmith.
-
B.
Stephen Haise
Stephen Haise is the son of American astronaut Fred Haise, one of the Apollo 13 crew members.
-
C.
Scott Sullivan
Scott Sullivan is the former WorldCom chief financial officer who became a central figure in one of the largest accounting fraud scandals in U.S. corporate history.
-
D.
Jeff Kirschenbaum
Jeff Kirschenbaum is a Hollywood film producer known for working on major studio features, including big-budget family and action movies.
-
E.
Phil Wenneck
Phil Wenneck is a charismatic, fast-talking schoolteacher and member of the "Wolfpack" whose misadventures drive much of the comedy in The Hangover film series.
- 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_69c008d9f4348190ab598a2913259a1c |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0685265208190b2204bd4abff2668 |
completed | March 22, 2026, 10:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c62daf2f408190923d67bd0222d2bb |
completed | March 27, 2026, 7:11 a.m. |
Created at: March 22, 2026, 4:33 p.m.