Triple
T18334316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Totale! |
E439228
|
entity |
| Predicate | starred |
P5563
|
FINISHED |
| Object | Miou-Miou |
—
|
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: Miou-Miou | Statement: [La Totale!, starred, Miou-Miou]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Miou-Miou Context triple: [La Totale!, starred, Miou-Miou]
-
A.
Miou-Miou
chosen
Miou-Miou is a French actress known for her versatile performances in films such as "Going Places" and "Entre Nous," which established her as a prominent figure in European cinema.
-
B.
Chéri
Chéri is a 1920 novel by French author Colette that portrays the complex, bittersweet relationship between a young man and an older courtesan in Belle Époque Paris.
-
C.
La Chinoise
La Chinoise is a 1967 French New Wave film by Jean-Luc Godard that satirically explores youthful Maoist radicalism in Paris on the eve of the 1968 student protests.
-
D.
Pour elle
Pour elle is a 2008 French thriller film about a man who devises an elaborate plan to break his wrongfully imprisoned wife out of jail.
-
E.
Mon homme
Mon homme is a French film known in English as "My Man."
- 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_69d8b9175fec8190af865699b4e64d8c |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50ecc91148190aa820fcd466009ce |
completed | April 19, 2026, 5:20 p.m. |
Created at: April 10, 2026, 10:36 a.m.