Triple
T21318494
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Snowden |
E525542
|
entity |
| Predicate | producer |
P490
|
FINISHED |
| Object | Philip Schulz-Deyle |
—
|
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: Philip Schulz-Deyle | Statement: [Snowden, producer, Philip Schulz-Deyle]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Philip Schulz-Deyle Context triple: [Snowden, producer, Philip Schulz-Deyle]
-
A.
Philip Schulz-Deyle
chosen
Philip Schulz-Deyle is a film producer known for his work on major feature films, including the political thriller "Snowden" (2016).
-
B.
Michael Fuchs
Michael Fuchs is an actor known for his role in the independent drama film "12 and Holding."
-
C.
Paul Schulze
Paul Schulze is an American character actor best known for his roles in television series such as "Nurse Jackie," "The Sopranos," and "24."
-
D.
Paul Schulze
Paul Schulze was an architect known for his work on notable public buildings, including contributions to major exhibition and museum structures in the United States.
-
E.
Philip Steuer
Philip Steuer is a film producer best known for his work on major studio projects, including the Disney drama "Saving Mr. Banks."
- 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_69e0b51ad810819098c12392c8e55f6c |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e77ece1c348190aaa9c52474b57b2f |
completed | April 21, 2026, 1:42 p.m. |
Created at: April 16, 2026, 4:37 p.m.