Triple
T21526783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Prince and Me |
E531117
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Craig Baumgarten |
—
|
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: Craig Baumgarten | Statement: [The Prince and Me, producer, Craig Baumgarten]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Craig Baumgarten Context triple: [The Prince and Me, producer, Craig Baumgarten]
-
A.
Craig Baumgarten
chosen
Craig Baumgarten is an American film producer known for working on action and drama movies, including mainstream Hollywood releases.
-
B.
Alan Baumgarten
Alan Baumgarten is an American film editor known for his work on a variety of feature films and television projects.
-
C.
Mark Rosenthal
Mark Rosenthal is an American screenwriter known for co-writing major Hollywood films, including contributing to the story for "Star Trek VI: The Undiscovered Country."
-
D.
Jay Polstein
Jay Polstein is a film producer best known for his work on the biographical drama "Frida."
-
E.
Eric Siegel
Eric Siegel is an American actor and television writer best known for his work on series such as "The Goldbergs."
- 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_69e0c45d95a081908e7962ad215da746 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee88515874819085e251c0d297a587 |
completed | April 26, 2026, 9:49 p.m. |
Created at: April 16, 2026, 6:26 p.m.