Triple
T5342353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Requiem for a Dream |
E123972
|
entity |
| Predicate | editor |
P1954
|
FINISHED |
| Object | Jay Rabinowitz |
E273214
|
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: Jay Rabinowitz | Statement: [Requiem for a Dream, editor, Jay Rabinowitz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jay Rabinowitz Context triple: [Requiem for a Dream, editor, Jay Rabinowitz]
-
A.
Jay Rabinowitz
chosen
Jay Rabinowitz is a film editor known for his work on numerous feature films, including the science-fiction thriller "The Adjustment Bureau."
-
B.
Jack Rabinovitch
Jack Rabinovitch was a Canadian businessman and philanthropist best known for creating one of Canada’s most prestigious literary awards, the Giller Prize.
-
C.
Jason Rubin
Jason Rubin is an American video game designer and co-founder of Naughty Dog, best known for his work on the Crash Bandicoot series.
-
D.
Jon Rubinstein
Jon Rubinstein is an American computer engineer and executive best known for his key role in developing Apple's iPod and later leading Palm as CEO.
-
E.
Andrew Rabinovich
Andrew Rabinovich is a computer scientist and researcher known for his contributions to computer vision and deep learning, including influential work at Google.
- 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_69bd464b07f8819095aa76577c9829e4 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd85cc5a9881909e23bf9c5b697a8e |
completed | March 20, 2026, 5:37 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c0b0779eec81909793446efb2ce749 |
completed | March 23, 2026, 3:16 a.m. |
Created at: March 20, 2026, 2:01 p.m.