Triple

T21252951
Position Surface form Disambiguated ID Type / Status
Subject Willa Holland E523790 entity
Predicate film P9968 FINISHED
Object Legion E123981 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: Legion | Statement: [Willa Holland, film, Legion]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Legion
Context triple: [Willa Holland, film, Legion]
  • A. Legion
    Legion is the nickname of Birmingham Legion FC, a professional soccer club based in Birmingham, Alabama, competing in the USL Championship.
  • B. Legion chosen
    "Legion" is a 2010 supernatural action-horror film in which archangel Michael defies God to protect humanity from an impending apocalypse.
  • C. Legion
    Legion is Lenovo's gaming-focused brand of high-performance laptops, desktops, and related PC hardware.
  • D. Legion
    Legion is a 1983 horror novel by William Peter Blatty that serves as a philosophical and supernatural sequel to The Exorcist, following Lieutenant Kinderman as he investigates a series of bizarre murders.
  • E. Legion
    Legion is a major Path of Exile expansion that introduced time-frozen armies from Wraeclast’s past, emphasizing large-scale combat and rewarding encounters.
  • 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_69e0b5146c108190adc9adb73e90abff completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7359f5b408190b951adddba83c97a completed April 21, 2026, 8:30 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0997f6a5908190958598492a1363e8 completed May 17, 2026, 10:27 a.m.
Created at: April 16, 2026, 3:57 p.m.