Triple

T4156948
Position Surface form Disambiguated ID Type / Status
Subject 92nd Academy Awards E91436 entity
Predicate bestOriginalScoreWinner P10678 FINISHED
Object Joker E38375 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: Joker | Statement: [92nd Academy Awards, bestOriginalScoreWinner, Joker]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Joker
Context triple: [92nd Academy Awards, bestOriginalScoreWinner, Joker]
  • A. Joker chosen
    Joker is a 2019 psychological thriller film centered on the origin story of Batman’s iconic nemesis, depicting his descent into madness and violence in a gritty, character-driven narrative.
  • B. Joker
    Joker is the masked protagonist of Persona 5, a stylish phantom thief who leads the Phantom Thieves of Hearts and wields dual personas in battle.
  • C. Joker
    Joker is a DC Comics–themed roller coaster at Six Flags México known for its chaotic, unpredictable ride experience.
  • D. Bane
    Bane is a formidable masked villain in the Batman universe, known for his immense physical strength, strategic genius, and role as one of Batman’s most dangerous adversaries.
  • E. Joker's Jinx
    Joker's Jinx is a high-speed, launched steel roller coaster themed to the DC Comics villain and located at Six Flags America in Maryland.
  • 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_69aed9626ebc8190a39de631788bea3e completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69af028fc11c819093fb2f616b97a694 completed March 9, 2026, 5:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69b589e9ff288190a8dfb62d32a330b5 completed March 14, 2026, 4:16 p.m.
Created at: March 9, 2026, 3:44 p.m.