Triple

T33235201
Position Surface form Disambiguated ID Type / Status
Subject The Abbess (plate) E850806 entity
Predicate visualContrastBetween P123206 FINISHED
Object ecclesiastical dignity and skeletal Death 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: ecclesiastical dignity and skeletal Death | Statement: [The Abbess (plate), visualContrastBetween, ecclesiastical dignity and skeletal Death]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: visualContrastBetween
Context triple: [The Abbess (plate), visualContrastBetween, ecclesiastical dignity and skeletal Death]
  • A. contrastRatio
    Indicates the proportional difference in luminance or intensity between two visual elements being compared.
  • B. providesContrastWith chosen
    Indicates that one entity is used to highlight differences or distinctions when compared with another entity.
  • C. achievesContrast
    Indicates that one entity creates or enhances a visual or conceptual difference relative to another entity.
  • D. hasDensityContrast
    Indicates that one entity differs from another in material density, highlighting a contrast in how compact or dense they are.
  • E. themeContrast
    Indicates a relationship where two themes are compared or opposed to highlight their differences or tension.
  • 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_69f349613f988190a1eb75467d167122 completed April 30, 2026, 12:21 p.m.
NER Named-entity recognition batch_69f6dd3cc0648190a275812d6711275a completed May 3, 2026, 5:29 a.m.
PD Predicate disambiguation batch_69f6d82eaee081908f06a71546315aea completed May 3, 2026, 5:07 a.m.
Created at: May 1, 2026, 1:31 a.m.