Triple
T18252964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Le Convoyeur |
E437144
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Claude Perron |
—
|
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: Claude Perron | Statement: [Le Convoyeur, stars, Claude Perron]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Claude Perron Context triple: [Le Convoyeur, stars, Claude Perron]
-
A.
Claude Perron
chosen
Claude Perron is a French actress known for her roles in films such as "Amélie" and the television series "WorkinGirls."
-
B.
Serge Perron
Serge Perron is a Canadian film and television actor known for his supporting roles in various Canadian productions.
-
C.
Paul Perron
Paul Perron is a Canadian scholar and professor known for his work in French literature, semiotics, and literary theory.
-
D.
Pierre Houde
Pierre Houde is a prominent Canadian sportscaster best known as the longtime French-language play-by-play voice of the Montreal Canadiens.
-
E.
Michel Auclair
Michel Auclair was a French actor known for his work in mid-20th-century European and Hollywood films, often portraying suave or sophisticated characters.
- 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_69d8b913351c8190932b6a426de04b41 |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e4fd81ea3481909d96b5399f7a32b3 |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 10:33 a.m.