Triple
T2289790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burlesque |
E51475
|
entity |
| Predicate | screenplayBy |
P15305
|
FINISHED |
| Object | Steve Antin |
E301988
|
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: Steve Antin | Statement: [Burlesque, screenplayBy, Steve Antin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Steve Antin Context triple: [Burlesque, screenplayBy, Steve Antin]
-
A.
Steve Antin
chosen
Steve Antin is an American actor, screenwriter, and filmmaker best known for writing and directing the musical film "Burlesque."
-
B.
Mike Krieger
Mike Krieger is a Brazilian-American entrepreneur and software engineer best known as the co-founder and former CTO of the photo-sharing social media platform Instagram.
-
C.
Andy Lassner
Andy Lassner is a television producer best known for his long-running work on "The Ellen DeGeneres Show" and other major daytime talk shows.
-
D.
Steve Janaszak
Steve Janaszak is an American goaltender best known as a member of the "Miracle on Ice" 1980 U.S. Olympic ice hockey team.
-
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_69a88b09c644819090b503456d96bf70 |
completed | March 4, 2026, 7:42 p.m. |
| NER | Named-entity recognition | batch_69abc273b67c8190bcd96f9a484647ef |
completed | March 7, 2026, 6:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b01d0915148190b77b8a30fa3f796d |
completed | March 10, 2026, 1:30 p.m. |
Created at: March 4, 2026, 7:48 p.m.