Triple

T10073155
Position Surface form Disambiguated ID Type / Status
Subject Vaslav Nijinsky E213677 entity
Predicate notableWork P4 FINISHED
Object Jeux E260442 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: Jeux | Statement: [Vaslav Nijinsky, notableWork, Jeux]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jeux
Context triple: [Vaslav Nijinsky, notableWork, Jeux]
  • A. Jeux chosen
    Jeux is a short, impressionistic ballet by Claude Debussy, composed in 1912–1913 and known for its innovative orchestration and subtle, shifting harmonies.
  • B. Home Game
    Home Game is a non-fiction book by former NHL goaltender and author Ken Dryden that reflects on the culture, meaning, and personal impact of hockey in Canada.
  • C. Game
    Game is an American rapper, songwriter, and actor known for his role in revitalizing West Coast hip hop in the mid-2000s.
  • D. Oyun
    Oyun is a local government area in Kwara State, Nigeria, known for its administrative role and local communities within the state.
  • E. Game & Watch
    Game & Watch is a series of handheld electronic games created by Nintendo in the early 1980s, notable for their simple LCD screens and pioneering role in portable gaming.
  • 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_69ca839add308190b57d53b4ec21f2d0 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdd013c9d0819091ebe6fc399832de completed April 2, 2026, 2:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69d29ab376488190bfb3efdb3f240cca completed April 5, 2026, 5:24 p.m.
Created at: March 30, 2026, 8:59 p.m.