Triple

T15600328
Position Surface form Disambiguated ID Type / Status
Subject Halloween II E375012 entity
Predicate featuresCharacter P626 FINISHED
Object Dr. Sam Loomis E896834 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: Dr. Sam Loomis | Statement: [Halloween II, featuresCharacter, Dr. Sam Loomis]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dr. Sam Loomis
Context triple: [Halloween II, featuresCharacter, Dr. Sam Loomis]
  • A. Dr. Samuel Loomis chosen
    Dr. Samuel Loomis is a fictional psychiatrist and determined nemesis of the killer Michael Myers in the Halloween horror film franchise.
  • B. Sam Loomis
    Sam Loomis is a central character in Alfred Hitchcock's classic horror film "Psycho," known as Marion Crane's boyfriend who becomes involved in investigating her disappearance.
  • C. Silas Laurence Loomis
    Silas Laurence Loomis was a 19th-century American physician, inventor, and educator known for his contributions to medical science and technological innovation.
  • D. Ray Stantz
    Ray Stantz is a passionate, good-natured paranormal investigator and founding member of the Ghostbusters team, known for his childlike enthusiasm and deep knowledge of the supernatural.
  • E. Egon Brain
    Egon Brain is a music producer known for creating and shaping recorded tracks, likely within contemporary electronic or pop genres.
  • 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_69d85cce25008190b13b52745fbd719b completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e621fc4819097e8e85e7ddfdc6c completed April 16, 2026, 2:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff5f355ff48190a2c2c262c09e6de0 completed May 9, 2026, 4:22 p.m.
Created at: April 10, 2026, 4:12 a.m.