Triple

T23819097
Position Surface form Disambiguated ID Type / Status
Subject Temple of Zhou Gong E589178 entity
Predicate hasCanonicalSubject P152370 FINISHED
Object Duke of Zhou as cultural model of virtue and governance 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: Duke of Zhou as cultural model of virtue and governance | Statement: [Temple of Zhou Gong, hasCanonicalSubject, Duke of Zhou as cultural model of virtue and governance]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasCanonicalSubject
Context triple: [Temple of Zhou Gong, hasCanonicalSubject, Duke of Zhou as cultural model of virtue and governance]
  • A. hasCanonicalTopic chosen
    Indicates that something is associated with its primary or standard topic as officially recognized or most commonly accepted.
  • B. hasCanonicalReference
    Indicates that one entity serves as the authoritative or standard reference source for another entity.
  • C. hasCanonicalRepresentation
    Indicates that one entity is the standard or authoritative form in which another entity is represented.
  • D. hasCanonicalTerm
    Indicates that one term in a set is designated as the standard or authoritative form used to represent a concept or entity.
  • E. hasCanonicalCategory
    Indicates that something is associated with its standard or officially recognized category within a classification 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_69e25d18619081909c7fb89d8926f14a completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f1c7ad0ec88190bace5c3f00908b30 completed April 29, 2026, 8:56 a.m.
PD Predicate disambiguation batch_69f156036ad48190bc2ffdaf39218bcb completed April 29, 2026, 12:51 a.m.
Created at: April 17, 2026, 7:58 p.m.