Triple
T12700449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Little Big Shots |
E303446
|
entity |
| Predicate | executiveProducer |
P7225
|
FINISHED |
| Object | Jeff Kleeman |
E475728
|
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: Jeff Kleeman | Statement: [Little Big Shots, executiveProducer, Jeff Kleeman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jeff Kleeman Context triple: [Little Big Shots, executiveProducer, Jeff Kleeman]
-
A.
Jeff Kleeman
chosen
Jeff Kleeman is a film producer and screenwriter known for his work on major studio projects, including co-writing the 2015 adaptation of "The Man from U.N.C.L.E."
-
B.
Josh Kesselman
Josh Kesselman is a film and television producer best known for his work as an executive producer on projects such as the series "The Great."
-
C.
Chris Klein
Chris Klein is a former American professional soccer player who later became a sports executive, notably serving as president of Major League Soccer’s LA Galaxy.
-
D.
Chris Klein
Chris Klein is an American actor best known for his breakout role as Oz in the teen comedy film series "American Pie."
-
E.
Jeff Danna
Jeff Danna is a Canadian film composer known for his scores for movies such as The Boondock Saints and various animated and dramatic films.
- 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_69d7bdef90d48190b46b88270e780946 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d961ef65ac8190aedf9ade3a68e24e |
completed | April 10, 2026, 8:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6eac6153c81909adff921117718d8 |
completed | May 3, 2026, 6:27 a.m. |
Created at: April 9, 2026, 5:22 p.m.