Triple
T9459607
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Marie-José Nat |
E228107
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Marie-José Nat |
E228107
|
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: Marie-José Nat | Statement: [Marie-José Nat, name, Marie-José Nat]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Marie-José Nat Context triple: [Marie-José Nat, name, Marie-José Nat]
-
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-José Clivaz
Marie-José Clivaz is an educator and school leader best known for co-founding the international private school Collège du Léman in Switzerland.
-
C.
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.
-
D.
Maryse Alberti
Maryse Alberti is an acclaimed French cinematographer known for her work on independent and documentary films, including projects like "The Wrestler" and "Creed."
-
E.
Marlies Schild
Marlies Schild is a retired Austrian alpine ski racer renowned as one of the most successful slalom specialists in World Cup and Olympic history.
- 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_69ca843b123881909b0e60028475d12d |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7fc916348190aeb3874a89071677 |
completed | April 1, 2026, 8:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d122965aa48190bb35202b8dd0fdbd |
completed | April 4, 2026, 2:39 p.m. |
Created at: March 30, 2026, 7:52 p.m.