Triple
T17851691
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nathan Juran |
E445821
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Nathan Juran |
—
|
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: Nathan Juran | Statement: [Nathan Juran, name, Nathan Juran]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nathan Juran Context triple: [Nathan Juran, name, Nathan Juran]
-
A.
Nathan Juran
chosen
Nathan Juran was an Academy Award–winning art director and later film director known for his work on classic Hollywood productions and science fiction and fantasy films.
-
B.
Michael Jaffe
Michael Jaffe is an American television and film producer known for his work on numerous TV movies, series, and feature films.
-
C.
Philip Andelman
Philip Andelman is an American music video and commercial director known for his work with major artists across pop and rock music.
-
D.
Aaron Kandell
Aaron Kandell is an American screenwriter best known for co-writing Disney's animated feature film "Moana."
-
E.
Jonathan Hadary
Jonathan Hadary is an American stage and screen actor known for his work in Broadway productions and various film and television roles.
- 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_69d8b9f26f18819089c9e43250bee6ae |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e48fff6c288190a2b5e60b66c03ddc |
completed | April 19, 2026, 8:19 a.m. |
Created at: April 10, 2026, 10:17 a.m.