Triple
T22381349
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen & Slim |
E553281
|
entity |
| Predicate | editor |
P1954
|
FINISHED |
| Object | Pete Beaudreau |
—
|
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: Pete Beaudreau | Statement: [Queen & Slim, editor, Pete Beaudreau]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pete Beaudreau Context triple: [Queen & Slim, editor, Pete Beaudreau]
-
A.
Pete Beaudreau
chosen
Pete Beaudreau is a film editor best known for his work on the financial thriller "Margin Call."
-
B.
Pete Olson
Pete Olson is an American Republican politician who represented Texas's 22nd congressional district in the U.S. House of Representatives from 2009 to 2021.
-
C.
Russell Dykstra
Russell Dykstra is an Australian actor known for his work in film, television, and theatre, including acclaimed performances in Australian cinema.
-
D.
Mike Sweeney
Mike Sweeney is a former Major League Baseball first baseman and designated hitter best known for his standout career with the Kansas City Royals.
-
E.
Daryl Dawson
Daryl Dawson was an Australian jurist who served as a Justice of the High Court of Australia.
- 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_69e11e4c03248190a26a5060ea6973ee |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1582c05fc8190836ae008426177a5 |
completed | April 29, 2026, 1 a.m. |
Created at: April 16, 2026, 8:45 p.m.