Triple

T12287917
Position Surface form Disambiguated ID Type / Status
Subject The Execution of Mary Stuart E292877 entity
Predicate specialEffectsTechnique P104064 FINISHED
Object stop trick 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: stop trick | Statement: [The Execution of Mary Stuart, specialEffectsTechnique, stop trick]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: specialEffectsTechnique
Context triple: [The Execution of Mary Stuart, specialEffectsTechnique, stop trick]
  • A. specialEffectsBy
    Indicates that the special effects for something (such as a film, scene, or shot) are created or provided by a particular person or entity.
  • B. visualEffect
    Indicates that one entity produces, modifies, or is associated with a particular visual effect on another entity or within a scene.
  • C. specialEffectsPioneer
    Indicates that the subject is recognized for groundbreaking or innovative work in the field of special effects.
  • D. projectionEffect
    Indicates the visual or spatial transformation produced when something is projected from one surface, medium, or viewpoint onto another.
  • E. materialEffect
    Indicates that one material causes, influences, or brings about a change in the properties, behavior, or state of another material or system.
  • F. None of above. chosen

Provenance (4 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_69d6ab690ad081908c0ed3870ec82d53 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d9261e1570819084bb4fdb44aa6aea completed April 10, 2026, 4:32 p.m.
PD Predicate disambiguation batch_69d91c4d9a9c8190aeb7beaf9792d8f0 completed April 10, 2026, 3:50 p.m.
PDg Predicate description generation batch_69d9261b7f088190b69fe6961015fce3 completed April 10, 2026, 4:32 p.m.
Created at: April 8, 2026, 9:52 p.m.