Triple

T27102242
Position Surface form Disambiguated ID Type / Status
Subject Sankara Stones E686471 entity
Predicate visualEffectInFilm P16366 FINISHED
Object glow with internal light 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: glow with internal light | Statement: [Sankara Stones, visualEffectInFilm, glow with internal light]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: visualEffectInFilm
Context triple: [Sankara Stones, visualEffectInFilm, glow with internal light]
  • A. visualEffect chosen
    Indicates that one entity produces, modifies, or is associated with a particular visual effect on another entity or within a scene.
  • B. specialEffectsTechnique
    Indicates a relationship where a particular special effects method or process is used to create or enhance visual or auditory effects in a production.
  • C. filmicFunction
    Indicates the role or purpose that something serves within the structure, style, or narrative function of a film.
  • D. 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.
  • E. resolutionEffect
    Indicates the outcome, consequence, or change that results from a particular resolution, decision, or problem-solving action.
  • 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_69ef1489f8b481908e24a1985982bd26 completed April 27, 2026, 7:47 a.m.
NER Named-entity recognition batch_69f62d53ad58819080c5227c7a729d15 completed May 2, 2026, 4:58 p.m.
PD Predicate disambiguation batch_69f62c15952881908a5ea0c25904afec completed May 2, 2026, 4:53 p.m.
Created at: April 27, 2026, 8:48 a.m.