Triple
T22184946
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Règle du jeu |
E548269
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Julien Carette |
—
|
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: Julien Carette | Statement: [La Règle du jeu, stars, Julien Carette]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Julien Carette Context triple: [La Règle du jeu, stars, Julien Carette]
-
A.
Julien Carette
chosen
Julien Carette was a French character actor known for his comic roles in classic French cinema of the 1930s and 1940s.
-
B.
Nicolas Caron
Nicolas Caron was a member of the Caron family in 18th-century France, known primarily as a brother of the playwright and polymath Pierre-Augustin Caron de Beaumarchais.
-
C.
Julien Lacheray
Julien Lacheray is a film editor best known for his work on Michel Gondry’s visually inventive film "The Science of Sleep."
-
D.
Arnaud Vaillant
Arnaud Vaillant is a French fashion designer and co-founder of the innovative Paris-based label Coperni, known for its tech-inspired, sculptural womenswear.
-
E.
Olivier Bousquet
Olivier Bousquet is a French computer scientist and machine learning researcher known for his work on statistical learning theory and his leadership roles in industry AI research.
- 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_69e11e3e0c7c8190b30d278845e2497e |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12aa823888190829368de6db4aa91 |
completed | April 28, 2026, 9:46 p.m. |
Created at: April 16, 2026, 8:35 p.m.