Triple

T22596096
Position Surface form Disambiguated ID Type / Status
Subject Fathers and Daughters E574684 entity
Predicate starring P1507 FINISHED
Object Diane Kruger 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: Diane Kruger | Statement: [Fathers and Daughters, starring, Diane Kruger]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Diane Kruger
Context triple: [Fathers and Daughters, starring, Diane Kruger]
  • A. Diane Kruger chosen
    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."
  • B. Franka Potente
    Franka Potente is a German actress best known internationally for her breakout role in "Run Lola Run" and her appearances in the Bourne film series.
  • C. Laetitia Casta
    Laetitia Casta is a French supermodel and actress known for her work with major fashion houses and her roles in European cinema.
  • 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. Edwige Fenech
    Edwige Fenech is an Italian actress and film producer best known as a major star of 1970s giallo thrillers and sex-comedy 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_69e245bc11308190b69d794d5d1e0bb6 completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f16268cb54819084a0f27ec0473f35 completed April 29, 2026, 1:44 a.m.
Created at: April 17, 2026, 2:50 p.m.