Triple

T10608106
Position Surface form Disambiguated ID Type / Status
Subject Luc Besson E275928 entity
Predicate spouse P13 FINISHED
Object Maïwenn Le Besco E678040 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: Maïwenn Le Besco | Statement: [Luc Besson, spouse, Maïwenn Le Besco]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maïwenn Le Besco
Context triple: [Luc Besson, spouse, Maïwenn Le Besco]
  • A. Maïwenn chosen
    Maïwenn is a French actress and filmmaker known for her intense, character-driven dramas and acclaimed direction in contemporary French cinema.
  • B. Catherine Breillat
    Catherine Breillat is a French filmmaker and novelist known for her provocative, boundary-pushing explorations of sexuality, gender, and power.
  • C. Marylène Ferrand
    Marylène Ferrand is a French landscape architect known for her role in designing Paris’s Parc de Bercy.
  • D. Viviane Khondji
    Viviane Khondji is known as the spouse of acclaimed cinematographer Darius Khondji.
  • E. Agnès Godard
    Agnès Godard is a renowned French cinematographer celebrated for her long-standing collaboration with director Claire Denis and her distinctive, atmospheric visual style.
  • 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_69d6aaf948d88190806cc3a8c47a3fb2 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d6df4c38c881908f69bb757b8e03f5 completed April 8, 2026, 11:05 p.m.
NED1 Entity disambiguation (via context triple) batch_69d95eb726bc8190a8db7357bd126016 completed April 10, 2026, 8:33 p.m.
Created at: April 8, 2026, 7:32 p.m.