Triple

T10165184
Position Surface form Disambiguated ID Type / Status
Subject Bishop of Strängnäs E235187 entity
Predicate hasClericalCollar P42772 FINISHED
Object yes 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: yes | Statement: [Bishop of Strängnäs, hasClericalCollar, yes]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasClericalCollar
Context triple: [Bishop of Strängnäs, hasClericalCollar, yes]
  • A. hasClericalVestments chosen
    Indicates that one entity possesses or is associated with the clerical vestments (religious garments) of another entity.
  • B. hasClericalFunction
    Indicates that an entity performs, is responsible for, or is associated with a clerical or administrative function.
  • C. hasClergyType
    Indicates the specific category or role of clergy associated with an entity.
  • D. isClericIn
    Indicates that an entity serves or functions as a cleric within a specified organization, location, or group.
  • E. hasClericalDiscipline
    Indicates that an entity is subject to, or governed by, a particular set of clerical or religious disciplinary rules or practices.
  • 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_69ca84ceafd0819085828600e11bed6b completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cdec6b96dc8190ae37d0d28e4c393b completed April 2, 2026, 4:11 a.m.
PD Predicate disambiguation batch_69cd4ba795808190acc9124c98c6e40f completed April 1, 2026, 4:45 p.m.
Created at: March 30, 2026, 9:10 p.m.