Triple
T6840144
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Julie Gayet |
E157550
|
entity |
| Predicate | name |
P16
|
FINISHED |
| Object | Julie Gayet |
E157550
|
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: Julie Gayet | Statement: [Julie Gayet, name, Julie Gayet]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Julie Gayet Context triple: [Julie Gayet, name, Julie Gayet]
-
A.
Julie Gayet
chosen
Julie Gayet is a French actress and film producer known for her work in cinema and for her high-profile relationship with former French president François Hollande.
-
B.
Claudie Haigneré
Claudie Haigneré is a French physician, astronaut, and former government minister who became the first French woman in space and a prominent figure in European space exploration.
-
C.
Brigitte Marie-Claude Trogneux
Brigitte Marie-Claude Trogneux is a French former teacher and the First Lady of France, married to President Emmanuel Macron.
-
D.
Micheline Presle
Micheline Presle is a renowned French actress known for her prolific film and television career spanning from the 1940s onward.
-
E.
Claudine Longet
Claudine Longet is a French-born singer and actress known for her soft, breathy vocal style and appearances in 1960s American television and film.
- 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_69c6882c53608190b99aebef079b23bd |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d6b2ee248190991c3e827be75bb7 |
completed | March 27, 2026, 7:12 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c72fb4f80081908198c8270633d34a |
completed | March 28, 2026, 1:32 a.m. |
Created at: March 27, 2026, 2:19 p.m.