Triple
T19098347
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prix Romy Schneider |
E467464
|
entity |
| Predicate | notableRecipient |
P108
|
FINISHED |
| Object | Virginie Ledoyen |
—
|
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: Virginie Ledoyen | Statement: [Prix Romy Schneider, notableRecipient, Virginie Ledoyen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Virginie Ledoyen Context triple: [Prix Romy Schneider, notableRecipient, Virginie Ledoyen]
-
A.
Virginie Ledoyen
chosen
Virginie Ledoyen is a French actress known for her work in both French cinema and international films, including prominent roles in dramas and thrillers.
-
B.
Nelly Auteuil
Nelly Auteuil is the daughter of French actor and filmmaker Daniel Auteuil.
-
C.
Sandrine Kiberlain
Sandrine Kiberlain is a French actress and singer known for her acclaimed performances in both dramatic and comedic films.
-
D.
Jean Prat
Jean Prat was a legendary French rugby union player, widely regarded as one of France’s greatest, who starred as a flanker and captain for both the national team and Section Paloise in the mid-20th century.
-
E.
Melanie Thierry
Melanie Thierry is a French actress and former model known for her roles in both European cinema and international films.
- 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_69d8dd05ac4c8190b1967d8f97f3fb2f |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e36b279c819091a8d51f044bc644 |
completed | April 20, 2026, 8:27 a.m. |
Created at: April 10, 2026, 12:04 p.m.