Triple

T10180911
Position Surface form Disambiguated ID Type / Status
Subject Laetitia E236777 entity
Predicate notableBearer P458 FINISHED
Object Laetitia Casta
Laetitia Casta is a French supermodel and actress known for her work with major fashion houses and her roles in European cinema.
 E846345 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: Laetitia Casta | Statement: [Laetitia, notableBearer, Laetitia Casta]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Laetitia Casta
Context triple: [Laetitia, notableBearer, Laetitia Casta]
  • A. Sandrine Kiberlain
    Sandrine Kiberlain is a French actress and singer known for her acclaimed performances in both dramatic and comedic films.
  • B. Melanie Thierry
    Melanie Thierry is a French actress and former model known for her roles in both European cinema and international films.
  • 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. Nelly Auteuil
    Nelly Auteuil is the daughter of French actor and filmmaker Daniel Auteuil.
  • E. Diane Kruger
    Diane Kruger is a German-born actress and former fashion model best known for her roles in films such as "Troy," "Inglourious Basterds," and "National Treasure."
  • 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: Laetitia Casta
Triple: [Laetitia, notableBearer, Laetitia Casta]
Generated description
Laetitia Casta is a French supermodel and actress known for her work with major fashion houses and her roles in European cinema.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Laetitia Casta
Target entity description: Laetitia Casta is a French supermodel and actress known for her work with major fashion houses and her roles in European cinema.
  • A. Sandrine Kiberlain
    Sandrine Kiberlain is a French actress and singer known for her acclaimed performances in both dramatic and comedic films.
  • B. Melanie Thierry
    Melanie Thierry is a French actress and former model known for her roles in both European cinema and international films.
  • 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. Nelly Auteuil
    Nelly Auteuil is the daughter of French actor and filmmaker Daniel Auteuil.
  • E. Diane Kruger
    Diane Kruger is a German-born actress and former fashion model best known for her roles in films such as "Troy," "Inglourious Basterds," and "National Treasure."
  • 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_69ca84d7260c8190bfbec36762943f37 completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cded315f14819085727bd9b4363d10 completed April 2, 2026, 4:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69d301373a008190b8d39a8db4167e4f completed April 6, 2026, 12:41 a.m.
NEDg Description generation batch_69d3028994fc81908507449a10e7e093 completed April 6, 2026, 12:47 a.m.
NED2 Entity disambiguation (via description) batch_69d3031ed1e88190b9906338285a6e46 completed April 6, 2026, 12:49 a.m.
Created at: March 30, 2026, 9:11 p.m.