Triple
T5717934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniel Auteuil |
E126066
|
entity |
| Predicate | hasChild |
P369
|
FINISHED |
| Object |
Nelly Auteuil
Nelly Auteuil is the daughter of French actor and filmmaker Daniel Auteuil.
|
E546363
|
NE FINISHED |
How this triple was built (4 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: Nelly Auteuil | Statement: [Daniel Auteuil, hasChild, Nelly Auteuil]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Nelly Auteuil Context triple: [Daniel Auteuil, hasChild, Nelly Auteuil]
-
A.
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.
-
B.
Élisabeth Depardieu
Élisabeth Depardieu is a French actress and film producer, known for her work in French cinema and her former marriage to actor Gérard Depardieu.
-
C.
Melanie Thierry
Melanie Thierry is a French actress and former model known for her roles in both European cinema and international films.
-
D.
Juliette Binoche
Juliette Binoche is an acclaimed French actress known for her nuanced performances in international cinema and her Academy Award-winning role in "The English Patient."
-
E.
Brigitte Marie-Claude Trogneux
Brigitte Marie-Claude Trogneux is a French former teacher and the First Lady of France, married to President Emmanuel Macron.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Nelly Auteuil Triple: [Daniel Auteuil, hasChild, Nelly Auteuil]
Generated description
Nelly Auteuil is the daughter of French actor and filmmaker Daniel Auteuil.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Nelly Auteuil Target entity description: Nelly Auteuil is the daughter of French actor and filmmaker Daniel Auteuil.
-
A.
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.
-
B.
Élisabeth Depardieu
Élisabeth Depardieu is a French actress and film producer, known for her work in French cinema and her former marriage to actor Gérard Depardieu.
-
C.
Melanie Thierry
Melanie Thierry is a French actress and former model known for her roles in both European cinema and international films.
-
D.
Juliette Binoche
Juliette Binoche is an acclaimed French actress known for her nuanced performances in international cinema and her Academy Award-winning role in "The English Patient."
-
E.
Brigitte Marie-Claude Trogneux
Brigitte Marie-Claude Trogneux is a French former teacher and the First Lady of France, married to President Emmanuel Macron.
- F. None of above. chosen
Provenance (5 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_69c0082e3d548190950169847b43043b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c024e084cc81909a652f7c10d32c32 |
completed | March 22, 2026, 5:20 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c097ebde448190806bb5bc7a2096fc |
completed | March 23, 2026, 1:31 a.m. |
| NEDg | Description generation | batch_69c09882e3188190a24199e5bcc7e76f |
completed | March 23, 2026, 1:33 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c0991cdc9c81908ef92c3dbfe4276a |
completed | March 23, 2026, 1:36 a.m. |
Created at: March 22, 2026, 3:46 p.m.