Triple

T35265
Position Surface form Disambiguated ID Type / Status
Subject Virgin Mary E698 entity
Predicate roleInTheology P2319 FINISHED
Object model of faith and discipleship 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: model of faith and discipleship | Statement: [Virgin Mary, roleInTheology, model of faith and discipleship]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: roleInTheology
Context triple: [Virgin Mary, roleInTheology, model of faith and discipleship]
  • A. role
    Indicates the function, position, or responsibility that one entity holds in relation to another within a given context.
  • B. playedRoleIn
    Indicates that an entity performed or assumed a specific role or character within a particular event, production, or context.
  • C. portrayedBy
    Indicates that one entity serves as the actor or performer who represents or plays the role of another entity in a work or medium.
  • D. monarchRole
    Indicates that an entity holds or is assigned the role, office, or position of a monarch in relation to a state or domain.
  • E. religiousTitle
    Indicates that one entity holds or is referred to by a specific religious rank, honorific, or clerical title in relation to another entity.
  • 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_69a2479dec388190967ba648663442c9 completed Feb. 28, 2026, 1:40 a.m.
NER Named-entity recognition batch_69a24989c3308190af59dfae37cfc32f completed Feb. 28, 2026, 1:48 a.m.
PD Predicate disambiguation batch_69a24873e97c8190b9e4279e43b6de14 completed Feb. 28, 2026, 1:44 a.m.
PDg Predicate description generation batch_69a24988d4688190b4584356ed7dea50 completed Feb. 28, 2026, 1:48 a.m.
Created at: Feb. 28, 2026, 1:44 a.m.