Triple

T3452170
Position Surface form Disambiguated ID Type / Status
Subject Audrey Tautou E72816 entity
Predicate name P16 FINISHED
Object Audrey Tautou E72816 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: Audrey Tautou | Statement: [Audrey Tautou, name, Audrey Tautou]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Audrey Tautou
Context triple: [Audrey Tautou, name, Audrey Tautou]
  • A. Audrey Tautou chosen
    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.
  • 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. Julie Delpy
    Julie Delpy is a French-American actress, filmmaker, and screenwriter best known for co-writing and starring in Richard Linklater’s "Before" trilogy.
  • 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. Melanie Thierry
    Melanie Thierry is a French actress and former model known for her roles in both European cinema and international films.
  • 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_69ad85b12a908190a1d10a6b03b4f8ae completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adbaa2f5ec81909ced93c01e8fe38b completed March 8, 2026, 6:06 p.m.
NED1 Entity disambiguation (via context triple) batch_69b360ef69308190a11f37ddbf3bbc7b completed March 13, 2026, 12:57 a.m.
Created at: March 8, 2026, 3:16 p.m.