Triple
T15711168
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Éric Toledano |
E380839
|
entity |
| Predicate | coDirector |
P17194
|
FINISHED |
| Object | Olivier Nakache |
E380838
|
NE FINISHED |
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: Olivier Nakache | Statement: [Éric Toledano, coDirector, Olivier Nakache]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Olivier Nakache Context triple: [Éric Toledano, coDirector, Olivier Nakache]
-
A.
Olivier Nakache
chosen
Olivier Nakache is a French film director and screenwriter best known for co-directing the internationally acclaimed comedy-drama "The Intouchables."
-
B.
Benoît Magimel
Benoît Magimel is a French actor known for his acclaimed performances in films such as "The Piano Teacher" and "La Haine."
-
C.
Andy Robin
Andy Robin is a screenwriter best known for co-writing the animated comedy film "Bee Movie."
-
D.
Agnès Jaoui
Agnès Jaoui is a French actress, screenwriter, and director known for her sharp, character-driven comedies and collaborations with Jean-Pierre Bacri.
-
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 (3 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_69d86d9bf930819082b30cf6d169297c |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e04f8f5d6081908243fa59b46b7c76 |
completed | April 16, 2026, 2:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff82f22fc88190820ecb171041136d |
completed | May 9, 2026, 6:54 p.m. |
Created at: April 10, 2026, 4:45 a.m.