Triple
T18334567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kindergarten Cop 2 |
E439236
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Bill Bellamy |
—
|
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: Bill Bellamy | Statement: [Kindergarten Cop 2, castMember, Bill Bellamy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bill Bellamy Context triple: [Kindergarten Cop 2, castMember, Bill Bellamy]
-
A.
Bill Bellamy
chosen
Bill Bellamy is an American stand-up comedian and actor known for his work on MTV in the 1990s and roles in films like "How to Be a Player" and "Love Jones."
-
B.
John Hough
John Hough is a British film and television director best known for his work in horror and genre cinema during the 1970s and 1980s.
-
C.
Bill Milner
Bill Milner is a British actor known for roles in films such as "Son of Rambow," "X-Men: First Class," and various television dramas.
-
D.
Tony Gillingham
Tony Gillingham is a wealthy and charming aristocrat in Downton Abbey who becomes one of Lady Mary Crawley’s principal suitors.
-
E.
Frank Bannister
Frank Bannister is a psychic investigator and con artist who can see and communicate with ghosts in the horror-comedy film "The Frighteners."
- 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_69d8b9175fec8190af865699b4e64d8c |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50ecc91148190aa820fcd466009ce |
completed | April 19, 2026, 5:20 p.m. |
Created at: April 10, 2026, 10:36 a.m.