Triple

T14854230
Position Surface form Disambiguated ID Type / Status
Subject W. (film) E349310 entity
Predicate editor P1954 FINISHED
Object Alexandre De Franceschi 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: Alexandre De Franceschi | Statement: [W. (film), editor, Alexandre De Franceschi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alexandre De Franceschi
Context triple: [W. (film), editor, Alexandre De Franceschi]
  • A. Alexandre de Franceschi chosen
    Alexandre de Franceschi is a film editor known for his work on the movie "Lion."
  • B. Jacques Defforey
    Jacques Defforey was a French businessman best known as one of the founders of the multinational retail corporation Carrefour.
  • C. Michel Dorigny
    Michel Dorigny was a 17th-century French painter and engraver associated with the Baroque style and the artistic circle of Simon Vouet in Paris.
  • D. André Flahaut
    André Flahaut is a Belgian politician who has held prominent national offices, including serving as President of the Chamber of Representatives.
  • E. Gérard de Battista
    Gérard de Battista is a French cinematographer known for his work on numerous European films, including the acclaimed drama "Monsieur Ibrahim."
  • 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_69d822ed7e1881909b90fca143ad7e34 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69ded44318f0819080b6c599f2d3474f completed April 14, 2026, 11:56 p.m.
Created at: April 10, 2026, 1:54 a.m.