Triple

T5751824
Position Surface form Disambiguated ID Type / Status
Subject Mattel Films E126870 entity
Predicate basedOnWorks P7125 FINISHED
Object UNO brand E491215 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: UNO brand | Statement: [Mattel Films, basedOnWorks, UNO brand]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: UNO brand
Context triple: [Mattel Films, basedOnWorks, UNO brand]
  • A. UNO
    UNO is a public research university in New Orleans, Louisiana, known for its diverse academic programs and strong ties to the city's culture and economy.
  • B. UNO
    UNO is a public research university located in Omaha, Nebraska, known for its urban campus and strong community engagement.
  • C. Sky Uno
    Sky Uno is an Italian pay-TV entertainment channel from Sky Italia known for airing popular talent shows, reality series, and variety programs.
  • D. ¡Uno! game chosen
    ¡Uno! is a fast-paced shedding-type card game where players race to discard all their cards by matching colors or numbers and using special action cards to disrupt opponents.
  • E. Monopoly
    Monopoly is a classic real-estate trading board game in which players buy, sell, and develop properties to bankrupt their opponents.
  • 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_69c00832aedc81909899801b141fa3b4 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0335f23c081909b35020801e3ef12 completed March 22, 2026, 6:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69c07e3a50b88190a943b2d91d3c5b8e completed March 22, 2026, 11:41 p.m.
Created at: March 22, 2026, 3:48 p.m.