Triple

T426899
Position Surface form Disambiguated ID Type / Status
Subject Congress of Racial Equality E9627 entity
Predicate religiousInfluence P2322 FINISHED
Object Christian pacifism 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: Christian pacifism | Statement: [Congress of Racial Equality, religiousInfluence, Christian pacifism]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: religiousInfluence
Context triple: [Congress of Racial Equality, religiousInfluence, Christian pacifism]
  • A. influencedReligion chosen
    Indicates that one entity has had a shaping or modifying effect on the religious beliefs, practices, or traditions of another entity.
  • B. religiousElement
    Indicates that something is a component, aspect, or feature associated with a religion or religious practice.
  • C. religiousCulturalContext
    Indicates the religious or cultural setting, tradition, or framework within which an entity, practice, or event occurs or is interpreted.
  • D. religiousTrend
    Indicates a pattern or direction of change over time in religious beliefs, practices, or affiliations among entities.
  • E. religiousTarget
    Indicates that an action, policy, or behavior is directed at someone or something specifically because of their religion or religious affiliation.
  • 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_69a2e801e1d48190b505d1dd336b52ac completed Feb. 28, 2026, 1:05 p.m.
NER Named-entity recognition batch_69a2eed691c4819092b7e57306114bbc completed Feb. 28, 2026, 1:34 p.m.
PD Predicate disambiguation batch_69a2edd6736c81909a6ca549f77b4345 completed Feb. 28, 2026, 1:29 p.m.
Created at: Feb. 28, 2026, 1:11 p.m.