Triple
T2522457
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Taxi (2004 film) |
E55553
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Stuart Levy |
E256404
|
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: Stuart Levy | Statement: [Taxi (2004 film), editedBy, Stuart Levy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stuart Levy Context triple: [Taxi (2004 film), editedBy, Stuart Levy]
-
A.
Jay O. Rothman
Jay O. Rothman is an American attorney and academic leader who serves as president of the University of Wisconsin System.
-
B.
Jonathan T. Taplin
Jonathan T. Taplin is an American film producer, media scholar, and author known for his work with director Martin Scorsese and his critiques of the digital economy.
-
C.
Melvin Shapiro
chosen
Melvin Shapiro is a film editor best known for his work on the musical fantasy film "Finian's Rainbow."
-
D.
Sanford Rothenberg
Sanford Rothenberg was the second husband of actress Fay Wray, known primarily for his marriage to the iconic King Kong star.
-
E.
David F. Levi
David F. Levi is an American legal scholar and former federal judge who served as dean of Duke University School of Law.
- 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_69ab49e4749c8190813311efd1630f1b |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd23895348190bb4dad6d7174893a |
completed | March 7, 2026, 7:22 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af2ba96a0c819091efd6d4ccf95ea5 |
completed | March 9, 2026, 8:20 p.m. |
Created at: March 6, 2026, 9:46 p.m.