Triple

T22757880
Position Surface form Disambiguated ID Type / Status
Subject José Lectoure E562899 entity
Predicate employer P7 FINISHED
Object Luna Park 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: Luna Park | Statement: [José Lectoure, employer, Luna Park]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Luna Park
Context triple: [José Lectoure, employer, Luna Park]
  • A. Luna Park chosen
    Luna Park is a historic indoor arena in Buenos Aires, Argentina, renowned for hosting major sports events, concerts, and cultural spectacles.
  • B. Luna Park
    Luna Park is a historic amusement park on Coney Island in Brooklyn, New York, known for its classic rides, carnival atmosphere, and role in early American amusement history.
  • C. Luna Park
    Luna Park is a 1992 Russian drama film by Pavel Lungin that explores nationalism, identity, and post-Soviet social tensions through the story of a neo-Nazi youth who discovers his Jewish heritage.
  • D. Luna Park amusement park
    Luna Park amusement park is a seaside funfair in Cap d’Agde, France, featuring a variety of rides, games, and family-friendly attractions.
  • E. Luna Park Sydney
    Luna Park Sydney is a historic harbourside amusement park in Sydney, Australia, famous for its iconic smiling entrance face and classic carnival rides.
  • 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_69e24551ec7881909a9c924dbea155f6 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f17a798ae08190b9810bf241613198 completed April 29, 2026, 3:26 a.m.
Created at: April 17, 2026, 3:25 p.m.