Triple

T20589895
Position Surface form Disambiguated ID Type / Status
Subject Substitutiary Locomotion E505889 entity
Predicate fictionalDiscipline P87724 FINISHED
Object witchcraft LITERAL 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: witchcraft | Statement: [Substitutiary Locomotion, fictionalDiscipline, witchcraft]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: fictionalDiscipline
Context triple: [Substitutiary Locomotion, fictionalDiscipline, witchcraft]
  • A. fictionalScientificField
    Indicates that an entity is associated with a scientific field that exists only in fiction rather than in real-world science.
  • B. fictionalEducation
    Indicates that one entity has an educational background, training, or schooling that exists only within a fictional or imaginary context relative to another entity.
  • C. fictionalGenre
    Indicates that a work of fiction belongs to or is categorized under a particular narrative genre or style.
  • D. fictionalField chosen
    Indicates that the subject is associated with a fictional or imaginary field, domain, or area rather than a real-world one.
  • E. fictionalInvention
    Indicates that one entity is an invention or creation that exists only within the fictional context of another entity (such as a story, universe, or work).
  • F. None of above.

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_69e0b4b9669c8190b8e81fc72817d42c completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6a979e4a48190a948165fb0f3b265 completed April 20, 2026, 10:32 p.m.
PD Predicate disambiguation batch_69e59fffe1748190825e4eaa90340631 completed April 20, 2026, 3:39 a.m.
Created at: April 16, 2026, 11:40 a.m.