Triple
T21092681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bienvenue chez les Ch’tis |
E519674
|
entity |
| Predicate | writer |
P1360
|
FINISHED |
| Object | Dany Boon |
—
|
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: Dany Boon | Statement: [Bienvenue chez les Ch’tis, writer, Dany Boon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dany Boon Context triple: [Bienvenue chez les Ch’tis, writer, Dany Boon]
-
A.
Dany Boon
chosen
Dany Boon is a French comedian, actor, and filmmaker best known for his popular comedy films such as "Bienvenue chez les Ch'tis."
-
B.
Chris Renaud
Chris Renaud is an American animator and film director best known for co-directing popular animated features such as Despicable Me and The Lorax.
-
C.
Andy Robin
Andy Robin is a screenwriter best known for co-writing the animated comedy film "Bee Movie."
-
D.
Olivier Nakache
Olivier Nakache is a French film director and screenwriter best known for co-directing the internationally acclaimed comedy-drama "The Intouchables."
-
E.
Michel Zitt
Michel Zitt is a prominent French scholar in scientometrics and research evaluation, recognized internationally for his influential contributions to the quantitative study of science and technology.
- 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_69e0b507dd9081908fb8bfcbef4c8b46 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e70950a31c8190bde2d7b414c362c7 |
completed | April 21, 2026, 5:21 a.m. |
Created at: April 16, 2026, 2:51 p.m.