Triple

T3681369
Position Surface form Disambiguated ID Type / Status
Subject Broken Flowers E78118 entity
Predicate starring P1507 FINISHED
Object Julie Delpy E152859 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: Julie Delpy | Statement: [Broken Flowers, starring, Julie Delpy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Julie Delpy
Context triple: [Broken Flowers, starring, Julie Delpy]
  • A. Julie Delpy chosen
    Julie Delpy is a French-American actress, filmmaker, and screenwriter best known for co-writing and starring in Richard Linklater’s "Before" trilogy.
  • B. 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."
  • C. Audrey Tautou
    Audrey Tautou is a French actress best known internationally for her lead role in the film "Amélie" and for starring in several major French and Hollywood productions.
  • D. 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.
  • E. Jeanne Tripplehorn
    Jeanne Tripplehorn is an American actress known for her film debut in the thriller "Basic Instinct" and prominent roles in movies like "The Firm" and the TV series "Big Love."
  • 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_69ad85e18c1c8190be8aafb227f39f48 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc492aed481909e8986378ad283fc completed March 8, 2026, 6:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4c3ae61908190beefd0df317b5eca completed March 14, 2026, 2:10 a.m.
Created at: March 8, 2026, 3:25 p.m.