Triple

T9319816
Position Surface form Disambiguated ID Type / Status
Subject Helen Eliza Benson Garrison E224217 entity
Predicate religiousOrEthicalBackground P9028 FINISHED
Object reformist Protestant milieu 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: reformist Protestant milieu | Statement: [Helen Eliza Benson Garrison, religiousOrEthicalBackground, reformist Protestant milieu]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: religiousOrEthicalBackground
Context triple: [Helen Eliza Benson Garrison, religiousOrEthicalBackground, reformist Protestant milieu]
  • A. religiousCulturalContext chosen
    Indicates the religious or cultural setting, tradition, or framework within which an entity, practice, or event occurs or is interpreted.
  • B. religionOrBelief
    Indicates that one entity holds, practices, or is associated with a particular religion, faith, or belief system.
  • C. religiousAttitude
    Indicates an entity’s stance, disposition, or orientation toward religion or religious beliefs.
  • D. religiousFoundation
    Indicates that an entity was established, created, or founded by a religious organization, authority, or tradition.
  • E. religiousTopicAddressed
    Indicates that a subject deals with, discusses, or focuses on a religious theme, issue, or question.
  • 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_69ca8426d48481909596360f7791c7dd completed March 30, 2026, 2:09 p.m.
NER Named-entity recognition batch_69cd358c7d348190a10fd8670d7756f5 completed April 1, 2026, 3:11 p.m.
PD Predicate disambiguation batch_69cc7a61e9a4819096eb014f3791ef2e completed April 1, 2026, 1:52 a.m.
Created at: March 30, 2026, 7:38 p.m.