Triple
T21875749
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Le Miroir à deux faces |
E540140
|
entity |
| Predicate | mainCharacter |
P1183
|
FINISHED |
| Object | Marie-José |
—
|
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: Marie-José | Statement: [Le Miroir à deux faces, mainCharacter, Marie-José]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marie-José Context triple: [Le Miroir à deux faces, mainCharacter, Marie-José]
-
A.
Marie-José Nat
chosen
Marie-José Nat was a French film and television actress known for her nuanced performances in mid-20th-century European cinema.
-
B.
Marie-France Pisier
Marie-France Pisier was a French actress and screenwriter renowned for her work in auteur cinema from the 1960s onward, notably in films by François Truffaut and André Téchiné.
-
C.
Marie-José Pérec
Marie-José Pérec is a French sprinter and three-time Olympic champion, best known for dominating the 200m and 400m events in the 1990s.
-
D.
Carine Petit
Carine Petit is a French politician who serves as the mayor of Paris's 14th arrondissement.
-
E.
Marie-José Tramini
Marie-José Tramini was a French-born artist and the second wife of Mexican Nobel laureate poet Octavio Paz, known for her work in collage and visual arts.
- 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_69e0c479a98081908ce333853fdd4348 |
completed | April 16, 2026, 11:14 a.m. |
| NER | Named-entity recognition | batch_69f0f33957f481908789b054a4fd1b77 |
completed | April 28, 2026, 5:49 p.m. |
Created at: April 16, 2026, 7:02 p.m.