Triple
T22899623
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Catch a Fire |
E568272
|
entity |
| Predicate | starredActor |
P5563
|
FINISHED |
| Object | Michele Burgers |
—
|
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: Michele Burgers | Statement: [Catch a Fire, starredActor, Michele Burgers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Michele Burgers Context triple: [Catch a Fire, starredActor, Michele Burgers]
-
A.
Michele Burgers
chosen
Michele Burgers is an actress known for her role in the 2006 political thriller film "Catch a Fire."
-
B.
Jeff Burger
Jeff Burger is a relatively obscure individual whose name is notably associated with the surname "Burger," but who has no widely recognized public profile or achievements documented in major reference sources.
-
C.
Stephan Burger
Stephan Burger is a German Roman Catholic prelate who serves as the Archbishop of Freiburg.
-
D.
Luigi Burger
Luigi Burger is a themed hamburger likely inspired by the Nintendo character Luigi, often paired or marketed alongside a corresponding Mario Burger.
-
E.
Grant Cramer
Grant Cramer is an American actor and producer best known for his roles in 1980s films such as "Hardbodies" and "Killer Klowns from Outer Space."
- 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_69e2458c23ec81908fa2570692c6614f |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f180155b1c8190a83eb6ec45387a1a |
completed | April 29, 2026, 3:50 a.m. |
Created at: April 17, 2026, 3:41 p.m.