Triple

T662923
Position Surface form Disambiguated ID Type / Status
Subject Aunt Polly E11795 entity
Predicate religiousAffiliationInFiction P45 FINISHED
Object Protestant Christianity 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: Protestant Christianity | Statement: [Aunt Polly, religiousAffiliationInFiction, Protestant Christianity]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: religiousAffiliationInFiction
Context triple: [Aunt Polly, religiousAffiliationInFiction, Protestant Christianity]
  • A. religiousAffiliation chosen
    Indicates that one entity has a specified religious association, belief system, or denominational membership.
  • B. religiousElement
    Indicates that something is a component, aspect, or feature associated with a religion or religious practice.
  • C. officialReligion
    Indicates that a particular religion is formally recognized and designated as the official or state religion of an entity (such as a country or region).
  • D. religiousTarget
    Indicates that an action, policy, or behavior is directed at someone or something specifically because of their religion or religious affiliation.
  • E. otherReligion
    Indicates that one entity follows or is associated with a religion that is different from the religion of another entity.
  • 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_69a4932862a0819098be659c814e4981 completed March 1, 2026, 7:27 p.m.
NER Named-entity recognition batch_69a49fd081e8819097f289961f5eff29 completed March 1, 2026, 8:21 p.m.
PD Predicate disambiguation batch_69a49d153a948190b3ccdc331ed33617 completed March 1, 2026, 8:09 p.m.
Created at: March 1, 2026, 7:36 p.m.