Triple
T20570330
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Police Academy 5: Assignment Miami Beach |
E505078
|
entity |
| Predicate | character |
P662
|
FINISHED |
| Object | Eric Lassard |
—
|
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: Eric Lassard | Statement: [Police Academy 5: Assignment Miami Beach, character, Eric Lassard]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Eric Lassard Context triple: [Police Academy 5: Assignment Miami Beach, character, Eric Lassard]
-
A.
Eric Lassard
chosen
Eric Lassard is the bumbling yet kind-hearted and eccentric commandant of the police academy in the Police Academy comedy film series.
-
B.
Paul Charbonnier
Paul Charbonnier was a French artist associated with the École de Nancy, a movement known for its contributions to Art Nouveau in the Lorraine region.
-
C.
Roger Bourgeois
Roger Bourgeois is an individual notable enough to be recognized as a prominent bearer of the Bourgeois surname.
-
D.
Michel Bizot
Michel Bizot is a Paris Métro station in the 12th arrondissement, named after the 19th-century French general Michel Brice Bizot.
-
E.
Michel Bouvier
Michel Bouvier is a biochemist and entrepreneur known for his pioneering work on G protein–coupled receptors (GPCRs) and for co-founding innovative drug discovery companies.
- 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_69e0b4b721588190993ac7b0a9be2736 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e6a7a5b0688190b45d0fa993c4765c |
completed | April 20, 2026, 10:24 p.m. |
Created at: April 16, 2026, 11:39 a.m.