Triple
T6977222
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wrapped in Red |
E161743
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Jesse Shatkin |
E291675
|
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: Jesse Shatkin | Statement: [Wrapped in Red, producer, Jesse Shatkin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jesse Shatkin Context triple: [Wrapped in Red, producer, Jesse Shatkin]
-
A.
Jesse Shatkin
chosen
Jesse Shatkin is a Grammy-nominated American record producer and songwriter known for his work with artists like Sia, Kelly Clarkson, and One Direction.
-
B.
Luke Shapiro
Luke Shapiro is the teenage marijuana dealer and emotionally troubled protagonist of the coming-of-age film "The Wackness," set in 1990s New York City.
-
C.
Jody Gerson
Jody Gerson is a prominent American music executive and producer, best known as the CEO and Chairman of Universal Music Publishing Group.
-
D.
Andrew Mondshein
Andrew Mondshein is an American film editor known for his work on acclaimed movies such as "Ma Rainey's Black Bottom" and "The Sixth Sense."
-
E.
Lewis Katz
Lewis Katz was an American businessman, philanthropist, and co-owner of the Philadelphia Inquirer known for his major charitable contributions to education and medicine.
- 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_69c68854a0d88190bc0bf82263f1afce |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6db677bbc8190a084b6951e5c3182 |
completed | March 27, 2026, 7:32 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c8029da4688190ae479d3f791aa1c2 |
completed | March 28, 2026, 4:32 p.m. |
Created at: March 27, 2026, 2:31 p.m.