Triple
T18888301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The First Nudie Musical |
E462014
|
entity |
| Predicate | cinematographyBy |
P1953
|
FINISHED |
| Object | Stephen M. Katz |
—
|
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: Stephen M. Katz | Statement: [The First Nudie Musical, cinematographyBy, Stephen M. Katz]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Stephen M. Katz Context triple: [The First Nudie Musical, cinematographyBy, Stephen M. Katz]
-
A.
Stephen M. Katz
chosen
Stephen M. Katz is an American cinematographer known for his work on a range of feature films and television projects, including the acclaimed drama "Gods and Monsters."
-
B.
Steven A. Katz
Steven A. Katz is an American screenwriter best known for writing the metafictional horror film "Shadow of the Vampire."
-
C.
Sidney Katz
Sidney Katz is a film editor known for his work in American cinema and for being part of a family of editors that includes Virginia Katz.
-
D.
Michael Katz
Michael Katz is a film producer best known for his work on acclaimed European art-house and independent films.
-
E.
Don Katz
Don Katz is an American entrepreneur and author best known as the founder of the audiobook and spoken-word entertainment company Audible.
- 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_69d8dcfc3430819095ee6fc0eb4c06a5 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5c478d8c481909291e7c471e5095a |
completed | April 20, 2026, 6:15 a.m. |
Created at: April 10, 2026, 11:58 a.m.