Triple

T10281243
Position Surface form Disambiguated ID Type / Status
Subject Letty Ortiz E241104 entity
Predicate enemyOf P437 FINISHED
Object Owen Shaw E559728 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: Owen Shaw | Statement: [Letty Ortiz, enemyOf, Owen Shaw]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Owen Shaw
Context triple: [Letty Ortiz, enemyOf, Owen Shaw]
  • A. Owen Shaw chosen
    Owen Shaw is a skilled and ruthless British mercenary and criminal mastermind who serves as a primary antagonist in the Fast & Furious film franchise.
  • B. Owen Davian
    Owen Davian is the ruthless and highly intelligent arms dealer who serves as the primary antagonist in the film "Mission: Impossible III."
  • C. Owen Moran
    Owen Moran was a prominent early 20th-century English featherweight boxer known for his toughness and for facing many of the era’s top fighters.
  • D. Owen Moore
    Owen Moore was an Irish-born American silent film actor best known for his early Hollywood work and his tumultuous marriage to screen star Mary Pickford.
  • E. Owen Moore
    Owen Moore is a supporting character in the video game The Last of Us Part II, known as a compassionate former Firefly and member of the WLF whose relationships and moral conflicts significantly impact the story’s emotional stakes.
  • 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_69d381a94c1881908fc38fc263d9b9c2 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4d2a177b48190aab7d7857f5bba7b completed April 7, 2026, 9:47 a.m.
NED1 Entity disambiguation (via context triple) batch_69d6f8352a108190b3692a2de3cb4dea completed April 9, 2026, 12:52 a.m.
Created at: April 6, 2026, 11:39 a.m.