Triple
T22010673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Spice World |
E543564
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Mark L. Rosen |
—
|
NE NERFINISHED |
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: Mark L. Rosen | Statement: [Spice World, producer, Mark L. Rosen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mark L. Rosen Context triple: [Spice World, producer, Mark L. Rosen]
-
A.
Mark L. Rosen
chosen
Mark L. Rosen is a film producer best known for his work on the romantic drama "Ice Castles."
-
B.
J. David Siegel
J. David Siegel is a film editor known for his work on major animated features, including the superhero comedy "DC League of Super-Pets."
-
C.
Howard Rosenman
Howard Rosenman is an American film producer known for his work on popular Hollywood movies and for helping bring LGBTQ themes into mainstream cinema.
-
D.
Jay O. Rothman
Jay O. Rothman is an American attorney and academic leader who serves as president of the University of Wisconsin System.
-
E.
Michael D. Rosenthal
Michael D. Rosenthal is a writer best known as the author whose work inspired the "Twilight Zone" episode "A Kind of Stopwatch."
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e2db934819095556760c7d85e4d |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127a4338c8190836074d21bfbaf78 |
completed | April 28, 2026, 9:33 p.m. |
Created at: April 16, 2026, 8:22 p.m.