Triple
T16569167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Code Black |
E402538
|
entity |
| Predicate | developer |
P73
|
FINISHED |
| Object | Michael Seitzman |
E254082
|
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: Michael Seitzman | Statement: [Code Black, developer, Michael Seitzman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michael Seitzman Context triple: [Code Black, developer, Michael Seitzman]
-
A.
Michael Seitzman
chosen
Michael Seitzman is an American screenwriter and producer known for his work on films such as "North Country" and for creating and producing several television series.
-
B.
Charles Roven
Charles Roven is an American film producer known for his work on major Hollywood blockbusters, including Christopher Nolan’s films such as Oppenheimer and The Dark Knight trilogy.
-
C.
Eric Weitz
Eric Weitz was a prominent historian known for his work on modern German and European history, genocide, and human rights.
-
D.
Patrick Seitz
Patrick Seitz is an American voice actor and ADR director known for his extensive work in anime, video games, and animation, including prominent roles in series like "Naruto," "Bleach," and "One Piece."
-
E.
John Seitz
John Seitz was an American cinematographer renowned for his influential work in classic Hollywood cinema, particularly in film noir and science fiction.
- 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_69d8838648088190acf97ef11fc3f61b |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e35773c00c819091731bebc02a69bb |
completed | April 18, 2026, 10:05 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00759424348190889dacbbc7435238 |
completed | May 10, 2026, 12:09 p.m. |
Created at: April 10, 2026, 5:16 a.m.