Triple

T20614292
Position Surface form Disambiguated ID Type / Status
Subject Rudimenta Hebraica E506523 entity
Predicate targetReligionContext P9028 FINISHED
Object Christian readership 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 readership | Statement: [Rudimenta Hebraica, targetReligionContext, Christian readership]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: targetReligionContext
Context triple: [Rudimenta Hebraica, targetReligionContext, Christian readership]
  • A. originReligionContext
    Indicates the religious background or setting from which something or someone originates or is derived.
  • B. religiousCulturalContext chosen
    Indicates the religious or cultural setting, tradition, or framework within which an entity, practice, or event occurs or is interpreted.
  • C. typicalReligionContext
    Indicates the usual or most common religious setting, tradition, or affiliation associated with an entity or situation.
  • D. religiousTarget
    Indicates that an action, policy, or behavior is directed at someone or something specifically because of their religion or religious affiliation.
  • E. associatedReligionOrBelief
    Indicates that an entity is connected to, identified with, or characterized by a particular religion or belief system.
  • 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_69e0b4bc90988190ac360aaf645efc1d completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6aada19e481909363428ceda67603 completed April 20, 2026, 10:38 p.m.
PD Predicate disambiguation batch_69e5a00c43308190b7ea58d559257e07 completed April 20, 2026, 3:39 a.m.
Created at: April 16, 2026, 11:41 a.m.