Triple

T11145022
Position Surface form Disambiguated ID Type / Status
Subject The Lovely Bones E263647 entity
Predicate producer P490 FINISHED
Object Aimee Peyronnet E859126 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: Aimee Peyronnet | Statement: [The Lovely Bones, producer, Aimee Peyronnet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Aimee Peyronnet
Context triple: [The Lovely Bones, producer, Aimee Peyronnet]
  • A. Aimee Peyronnet chosen
    Aimee Peyronnet is a film producer best known for her work on the 2009 adaptation of "The Lovely Bones."
  • B. Julie Bruneau
    Julie Bruneau was a 19th-century Canadian woman best known as the wife and close confidante of Louis-Joseph Papineau, the prominent Lower Canadian political leader and reformer.
  • C. Racquel Chevremont
    Racquel Chevremont is an American art curator, collector, and former model known for her work promoting Black and queer artists and for co-founding the curatorial collective Deux Femmes Noires.
  • D. Rachelle Lefevre
    Rachelle Lefevre is a Canadian actress best known for her roles in the Twilight film series and various American television dramas.
  • E. Danielle Savre
    Danielle Savre is an American actress best known for her starring role as firefighter Maya Bishop on the television drama series "Station 19."
  • 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_69d6aa9c0ba08190bbd19c217489b755 completed April 8, 2026, 7:21 p.m.
NER Named-entity recognition batch_69d7e8634d5481909b114d30a542ea3f completed April 9, 2026, 5:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69e496c152a081909c6ad8b2a6e41927 completed April 19, 2026, 8:48 a.m.
Created at: April 8, 2026, 9:28 p.m.