Triple

T3953191
Position Surface form Disambiguated ID Type / Status
Subject Surya Bonaly E84914 entity
Predicate name P16 FINISHED
Object Surya Bonaly E84914 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: Surya Bonaly | Statement: [Surya Bonaly, name, Surya Bonaly]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Surya Bonaly
Context triple: [Surya Bonaly, name, Surya Bonaly]
  • A. Surya Bonaly chosen
    Surya Bonaly is a French figure skater renowned for her powerful athleticism, multiple European titles, and for performing a historic backflip on one blade in Olympic competition.
  • B. Noëlle Boisson
    Noëlle Boisson is a French film editor known for her work on numerous acclaimed international films, including major historical and dramatic features.
  • C. Emmanuelle Vaugier
    Emmanuelle Vaugier is a Canadian actress and model known for her roles in film and television, including appearances in projects like "Two and a Half Men," "Smallville," and various genre films.
  • D. Nelly Roussel
    Nelly Roussel was a pioneering French feminist, neo-Malthusian activist, and orator known for her advocacy of birth control, women’s rights, and social reform in the early 20th century.
  • E. Maryse Alberti
    Maryse Alberti is an acclaimed French cinematographer known for her work on independent and documentary films, including projects like "The Wrestler" and "Creed."
  • 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_69aed934fbfc8190847068e4546de963 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aef93b8f5c8190bdb062a76b68b3e0 completed March 9, 2026, 4:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69b533ab58c08190ad83bf02571caaf2 completed March 14, 2026, 10:08 a.m.
Created at: March 9, 2026, 3:30 p.m.