Triple

T4626118
Position Surface form Disambiguated ID Type / Status
Subject Seven Years in Tibet E101100 entity
Predicate editedBy P1954 FINISHED
Object Noëlle Boisson E33008 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: Noëlle Boisson | Statement: [Seven Years in Tibet, editedBy, Noëlle Boisson]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Noëlle Boisson
Context triple: [Seven Years in Tibet, editedBy, Noëlle Boisson]
  • A. Noëlle Boisson chosen
    Noëlle Boisson is a French film editor known for her work on numerous acclaimed international films, including major historical and dramatic features.
  • B. Tiphaine Auzière
    Tiphaine Auzière is a French lawyer and political figure known both for her legal career and as the daughter of France’s First Lady, Brigitte Macron.
  • C. Aurélie Charillon
    Aurélie Charillon is a French local politician serving as the mayor of the commune of Prévessin-Moëns in eastern France.
  • D. Aurélie Dupont
    Aurélie Dupont is a renowned French ballerina and former étoile of the Paris Opera Ballet who later became the company’s artistic director.
  • E. Denise Baudu
    Denise Baudu is the young, determined saleswoman who serves as the central heroine of Émile Zola’s novel "Au Bonheur des Dames," embodying both the struggles and aspirations of women in the rise of the modern department store.
  • 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_69bd43d0497c8190ac23c65c5804846a completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd5a0a7b588190bc6552ee5babb198 completed March 20, 2026, 2:30 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdfaab30508190881828adab92ba22 completed March 21, 2026, 1:55 a.m.
Created at: March 20, 2026, 1:13 p.m.