Triple
T18685337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Dancer |
E456844
|
entity |
| Predicate | stars |
P1956
|
FINISHED |
| Object | Mélanie Thierry |
—
|
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: Mélanie Thierry | Statement: [The Dancer, stars, Mélanie Thierry]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mélanie Thierry Context triple: [The Dancer, stars, Mélanie Thierry]
-
A.
Melanie Thierry
chosen
Melanie Thierry is a French actress and former model known for her roles in both European cinema and international films.
-
B.
Nelly Auteuil
Nelly Auteuil is the daughter of French actor and filmmaker Daniel Auteuil.
-
C.
Virginie Ledoyen
Virginie Ledoyen is a French actress known for her work in both French cinema and international films, including prominent roles in dramas and thrillers.
-
D.
Carole Bouquet
Carole Bouquet is a French actress known for her roles in European art cinema and as a Bond girl in the James Bond film "For Your Eyes Only."
-
E.
Nathalie Delon
Nathalie Delon was a French actress and writer, best known for her role in the film "Le Samouraï" and her marriage to actor Alain Delon.
- 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_69d8d391eb488190ac2e9abf5bf255e4 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e55b2c58188190b906c9ab080a76ff |
completed | April 19, 2026, 10:46 p.m. |
Created at: April 10, 2026, 11:49 a.m.