Triple
T22051851
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Les Ripoux |
E544903
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object | Claude Zidi |
—
|
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 Zidi | Statement: [Les Ripoux, screenwriter, Claude Zidi]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Claude Zidi Context triple: [Les Ripoux, screenwriter, Claude Zidi]
-
A.
Claude Zidi
chosen
Claude Zidi is a French film director and screenwriter best known for his popular comedies and box-office hits from the 1970s through the 1990s.
-
B.
Didier Zokora
Didier Zokora is a retired Ivorian defensive midfielder best known for his long international career with Côte d'Ivoire and club spells at teams such as Tottenham Hotspur and Sevilla.
-
C.
Chedly Zouiten
Chedly Zouiten was a prominent Tunisian sports figure and football administrator after whom one of Tunis’s main stadiums is named.
-
D.
Elyaz Zidane
Elyaz Zidane is a French footballer and the youngest son of legendary former player and coach Zinedine Zidane.
-
E.
Zinedine Soualem
Zinedine Soualem is a French actor known for his extensive work in film, television, and theater, often appearing in French comedies and dramas.
- 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_69e11e32445c8190ab97089b48a130bb |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f1285513fc8190b691e1f57085956f |
completed | April 28, 2026, 9:36 p.m. |
Created at: April 16, 2026, 8:26 p.m.