Triple

T1420659
Position Surface form Disambiguated ID Type / Status
Subject Cathedral Chapter of Münster E30216 entity
Predicate typeOfCanonry P27580 FINISHED
Object secular canons 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: secular canons | Statement: [Cathedral Chapter of Münster, typeOfCanonry, secular canons]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: typeOfCanonry
Context triple: [Cathedral Chapter of Münster, typeOfCanonry, secular canons]
  • A. givesCanon
    Indicates that one entity provides or establishes an official or authoritative version (canon) of something for another entity or context.
  • B. inCanonOf
    Indicates that one entity is officially recognized as part of the established canon or authoritative body of works associated with another entity.
  • C. usesCanon
    Indicates that one entity employs or relies on another entity as its standard, reference, or authoritative source.
  • D. canonizedAs
    Indicates that an authority, typically a religious institution, has formally declared someone to be a saint or holy figure.
  • E. usesCanons
    Indicates that one entity employs or makes use of canons (such as rules, principles, or artillery pieces) in relation to another entity or context.
  • 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_69a498fb823c8190a67ce4c4837e641a completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c40764ec8190b85de6befcb20dda completed March 1, 2026, 10:56 p.m.
PD Predicate disambiguation batch_69a4bf060b0081909ba00e6ac093a28b completed March 1, 2026, 10:34 p.m.
PDg Predicate description generation batch_69a4c06721488190ac7f6e012f21af3d completed March 1, 2026, 10:40 p.m.
Created at: March 1, 2026, 7:59 p.m.