Triple
T23061820
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pater |
E574921
|
entity |
| Predicate | castMember |
P1668
|
FINISHED |
| Object | Vincent Lindon |
—
|
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: Vincent Lindon | Statement: [Pater, castMember, Vincent Lindon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vincent Lindon Context triple: [Pater, castMember, Vincent Lindon]
-
A.
Vincent Lindon
chosen
Vincent Lindon is a French film actor acclaimed for his intense, naturalistic performances in dramas and thrillers.
-
B.
Stephen Boyer
Stephen Boyer is one of the children of prominent American educator and former U.S. Commissioner of Education Ernest L. Boyer.
-
C.
Guy Ferland
Guy Ferland is an American film and television director known for his work on projects such as Dirty Dancing: Havana Nights and numerous acclaimed TV dramas.
-
D.
Michael Rapaport
Michael Rapaport is an American actor and comedian known for his prolific character roles in film and television, as well as his outspoken, humorous public persona.
-
E.
Peter Hermann
Peter Hermann is an American actor and producer best known for his roles on television series such as "Law & Order: Special Victims Unit" and "Younger."
- 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_69e245bd6e4c8190bb8942245b68cad5 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1899ff96081908d89a07a3b1065c8 |
completed | April 29, 2026, 4:31 a.m. |
Created at: April 17, 2026, 3:55 p.m.