Triple

T33446671
Position Surface form Disambiguated ID Type / Status
Subject Academy Award for Best Actor for American History X E856522 entity
Predicate associatedWithFilmTopic P206478 FINISHED
Object racism in the United States LITERAL 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: racism in the United States | Statement: [Academy Award for Best Actor for American History X, associatedWithFilmTopic, racism in the United States]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: associatedWithFilmTopic
Context triple: [Academy Award for Best Actor for American History X, associatedWithFilmTopic, racism in the United States]
  • A. subjectOfFilm
    Indicates that a person, character, or topic is the main focus or central topic depicted in a particular film.
  • B. associatedWithComposerOfFilm
    Indicates a relationship where an entity is connected to the composer who created the musical score for a specific film.
  • C. associatedWithLeadActorOfFilm
    Indicates a relationship where one entity is connected or linked in some relevant way to the lead actor of a specified film.
  • D. associatedWithProducerOfFilm
    Indicates that one entity has an association or connection with the producer of a particular film.
  • E. associatedWithAwardNominatedFilm
    Indicates that an entity has a relationship to a film that has been nominated for an award.
  • F. None of above. chosen

Provenance (4 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_69f34971b75881908be360bb041f003c completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_6a037c9141dc819098d7fcc36e69882c completed May 12, 2026, 7:16 p.m.
PD Predicate disambiguation batch_6a0379f505c88190ac0879ab422c3054 completed May 12, 2026, 7:05 p.m.
PDg Predicate description generation batch_6a037c7fb9f88190b384b1b68200aef0 completed May 12, 2026, 7:16 p.m.
Created at: May 1, 2026, 1:37 a.m.