Triple

T17803690
Position Surface form Disambiguated ID Type / Status
Subject Julie Covington E444498 entity
Predicate notableWork P4 FINISHED
Object The Devil's Crown NE NERFINISHED

How this triple was built (3 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 Devil's Crown | Statement: [Julie Covington, notableWork, The Devil's Crown]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Devil's Crown
Context triple: [Julie Covington, notableWork, The Devil's Crown]
  • A. Devil's End
    Devil's End is a fictional English village best known as the eerie, occult-infused setting of the Doctor Who serial "The Daemons."
  • B. The Devil Commands
    The Devil Commands is a 1941 American horror film in which a scientist’s experiments with communicating with the dead lead to terrifying consequences.
  • C. The Devil’s Nightmare
    The Devil’s Nightmare is a 1971 European horror film, also known as "La plus longue nuit du diable," featuring Daniel Emilfork in a memorable role within its demonic, gothic narrative.
  • D. The Accursed
    The Accursed is a Gothic historical novel by Joyce Carol Oates that blends supernatural horror with social and political commentary in early 20th-century Princeton, New Jersey.
  • E. The Devil’s Mask
    The Devil’s Mask is a 1946 mystery film adaptation of the popular radio serial "I Love a Mystery," featuring a suspenseful plot involving murder, intrigue, and a sinister Japanese mask.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: The Devil's Crown
Target entity description: The Devil's Crown is a 1978 BBC historical drama television series that chronicles the turbulent reigns of England’s early Plantagenet kings.
  • A. Devil's End
    Devil's End is a fictional English village best known as the eerie, occult-infused setting of the Doctor Who serial "The Daemons."
  • B. The Devil Commands
    The Devil Commands is a 1941 American horror film in which a scientist’s experiments with communicating with the dead lead to terrifying consequences.
  • C. The Devil’s Nightmare
    The Devil’s Nightmare is a 1971 European horror film, also known as "La plus longue nuit du diable," featuring Daniel Emilfork in a memorable role within its demonic, gothic narrative.
  • D. The Accursed
    The Accursed is a Gothic historical novel by Joyce Carol Oates that blends supernatural horror with social and political commentary in early 20th-century Princeton, New Jersey.
  • E. The Devil’s Mask
    The Devil’s Mask is a 1946 mystery film adaptation of the popular radio serial "I Love a Mystery," featuring a suspenseful plot involving murder, intrigue, and a sinister Japanese mask.
  • F. None of above. chosen

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_69d8b9efe370819095cd219b143ae727 completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e4880171608190be2088c7a387bfb7 completed April 19, 2026, 7:45 a.m.
Created at: April 10, 2026, 10:13 a.m.