Triple
T18943753
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Finding Steve McQueen |
E463452
|
entity |
| Predicate | starring |
P1507
|
FINISHED |
| Object | Jake Weary |
—
|
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: Jake Weary | Statement: [Finding Steve McQueen, starring, Jake Weary]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jake Weary Context triple: [Finding Steve McQueen, starring, Jake Weary]
-
A.
Jake Weary
chosen
Jake Weary is an American actor and musician best known for his role as Deran Cody on the television series "Animal Kingdom."
-
B.
Blayne Weaver
Blayne Weaver is an American actor, writer, and director best known for voicing Peter Pan in Disney projects and for his work in independent films.
-
C.
Josh Heird
Josh Heird is a collegiate athletics administrator who serves as the athletic director overseeing the University of Louisville’s sports programs.
-
D.
Joey Wells
Joey Wells is a screenwriter best known for co-writing the comedy film "Night School."
-
E.
Joey Wells
Joey Wells is a comedian and writer known for his collaborations with Kevin Hart, including appearances in Hart’s stand-up specials and related projects.
- 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_69d8dcfec90481909e926be9767e5779 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5d3ed847c8190a911a61673608a5c |
completed | April 20, 2026, 7:21 a.m. |
Created at: April 10, 2026, 11:59 a.m.