Triple
T14961535
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Big Night |
E373075
|
entity |
| Predicate | cinematographyBy |
P1953
|
FINISHED |
| Object | Ken Kelsch |
E943986
|
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: Ken Kelsch | Statement: [Big Night, cinematographyBy, Ken Kelsch]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ken Kelsch Context triple: [Big Night, cinematographyBy, Ken Kelsch]
-
A.
Ken Kelsch
chosen
Ken Kelsch was an American cinematographer and occasional producer known for his gritty visual style and frequent collaborations with director Abel Ferrara.
-
B.
Jim Kelch
Jim Kelch is an American sportscaster best known for his work as a play-by-play announcer on Cincinnati Reds radio broadcasts.
-
C.
Kevin Biegel
Kevin Biegel is an American television writer and producer best known for co-creating the sitcom Cougar Town and working on shows like Scrubs and Enlisted.
-
D.
Marc Klasfeld
Marc Klasfeld is an American music video director known for his prolific work with major hip-hop and rock artists and for creating visually distinctive, narrative-driven videos.
-
E.
Kevin Nolting
Kevin Nolting is an American film editor best known for his work on Pixar animated features, including the Academy Award-winning film "Up."
- 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_69d85cca979481908747d2a81eba1cea |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6cece6881908cd8c8fe41583bee |
completed | April 15, 2026, 12:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a009181980481908fb49e464aef8734 |
completed | May 10, 2026, 2:09 p.m. |
Created at: April 10, 2026, 2:40 a.m.