Triple
T22021082
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swingers |
E543847
|
entity |
| Predicate | characterPortrayedBy |
P1507
|
FINISHED |
| Object | Trent Walker – Vince Vaughn |
—
|
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: Trent Walker – Vince Vaughn | Statement: [Swingers, characterPortrayedBy, Trent Walker – Vince Vaughn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Trent Walker – Vince Vaughn Context triple: [Swingers, characterPortrayedBy, Trent Walker – Vince Vaughn]
-
A.
Vince Vaughn
chosen
Vince Vaughn is an American actor and comedian known for his roles in hit comedies such as "Wedding Crashers," "Dodgeball," and "Old School."
-
B.
Jon Walker
Jon Walker is an American musician and songwriter best known as the former bassist of the rock band Panic! at the Disco.
-
C.
Sam Vincent
Sam Vincent is a Canadian voice actor best known for his work in animated television series and films.
-
D.
Sam Vincent
Sam Vincent is a human software developer known for creating and contributing to technological projects.
-
E.
Fred Vaughn
Fred Vaughn is a minor character in Louisa May Alcott’s "Little Women," known as a wealthy young man within Amy March’s social circle.
- 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_69e11e2e8ea4819084210fe06d3a1b8d |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127c7b3308190ac056bef6f82722e |
completed | April 28, 2026, 9:33 p.m. |
Created at: April 16, 2026, 8:23 p.m.