Triple

T10198218
Position Surface form Disambiguated ID Type / Status
Subject 88th Academy Awards E238817 entity
Predicate bestActorWinner P8115 FINISHED
Object Leonardo DiCaprio E9770 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: Leonardo DiCaprio | Statement: [88th Academy Awards, bestActorWinner, Leonardo DiCaprio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Leonardo DiCaprio
Context triple: [88th Academy Awards, bestActorWinner, Leonardo DiCaprio]
  • A. Leonardo DiCaprio chosen
    Leonardo DiCaprio is an Academy Award–winning American actor and environmental activist known for his roles in films like Titanic, Inception, and The Revenant, as well as his prominent climate advocacy.
  • B. Adrien Brody
    Adrien Brody is an American actor best known for his Academy Award–winning performance in "The Pianist" and his diverse roles in both independent films and major Hollywood productions.
  • C. Brad Pitt
    Brad Pitt is an American actor and film producer renowned for his leading roles in major Hollywood films and for winning multiple Academy Awards.
  • D. Roger Winslet
    Roger Winslet is the father of acclaimed English actress Kate Winslet.
  • E. Edward Norton
    Edward Norton is an acclaimed American actor and filmmaker known for his intense, nuanced performances in films such as "Fight Club," "American History X," and "Birdman."
  • 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_69ca84e1ea088190b38162e43d4cfa8f completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdee3c44408190b09fa41f2d257c04 completed April 2, 2026, 4:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69d317e4a3308190b6ec4252bc55985d completed April 6, 2026, 2:18 a.m.
Created at: March 30, 2026, 9:13 p.m.