Triple

T10708371
Position Surface form Disambiguated ID Type / Status
Subject Dylan O'Brien E252468 entity
Predicate knownFor P22 FINISHED
Object The Outfit E724899 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: The Outfit | Statement: [Dylan O'Brien, knownFor, The Outfit]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Outfit
Context triple: [Dylan O'Brien, knownFor, The Outfit]
  • A. The Outfit chosen
    The Outfit is a 2022 crime thriller film centered on a meticulous English tailor in Chicago who becomes entangled with dangerous mobsters over the course of a tense night.
  • B. The Outfit
    The Outfit is a 1973 American crime film, based on a Donald E. Westlake novel, that follows a professional thief seeking revenge against a powerful criminal syndicate.
  • C. Stakeout
    "Stakeout" is a 1987 American buddy-cop comedy thriller film starring Richard Dreyfuss and Emilio Estevez as detectives assigned to surveil an escaped convict’s ex-girlfriend.
  • D. Machine Gun Corps
    The Machine Gun Corps was a specialized British Army unit formed during World War I to provide concentrated machine-gun fire support on the battlefield.
  • E. Stumptown
    Stumptown is a historic nickname for Portland, Oregon, referencing the city’s rapid 19th-century growth that left tree stumps scattered throughout the area.
  • 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_69d6aa5cbabc8190973e683950d89faf completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fe5063bc8190ba12fd68a59c9a03 completed April 9, 2026, 1:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69d9990760b48190a05753974cdf556c completed April 11, 2026, 12:42 a.m.
Created at: April 8, 2026, 9:13 p.m.