Triple

T21419021
Position Surface form Disambiguated ID Type / Status
Subject Halloween 4: The Return of Michael Myers E528381 entity
Predicate mainCharacter P1183 FINISHED
Object Michael Myers NE NERFINISHED

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: Michael Myers | Statement: [Halloween 4: The Return of Michael Myers, mainCharacter, Michael Myers]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Michael Myers
Context triple: [Halloween 4: The Return of Michael Myers, mainCharacter, Michael Myers]
  • A. Michael Myers chosen
    Michael Myers is the iconic masked serial killer from the "Halloween" horror film franchise.
  • B. Michael Scott Myers
    Michael Scott Myers is an American screenwriter best known for adapting the memoir "The Whole Wide World" into the 1996 film of the same name.
  • C. Jason Voorhees
    Jason Voorhees is a fictional, hockey mask–wearing serial killer and horror icon best known as the central antagonist of the Friday the 13th slasher film series.
  • D. Freddy Krueger
    Freddy Krueger is a fictional supernatural serial killer known for haunting and murdering teenagers in their dreams, recognizable by his burned face, bladed glove, and striped sweater.
  • E. Willis Hale
    Willis Hale was an American architect known for his highly ornate and eccentric Victorian-era buildings in Philadelphia.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0c454c248819093425d1099101c09 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69e8b2ccddc08190b4f66fa6ccda41e2 completed April 22, 2026, 11:36 a.m.
Created at: April 16, 2026, 5:47 p.m.