Triple

T28631848
Position Surface form Disambiguated ID Type / Status
Subject Wenzhong E724660 entity
Predicate honorsCulture P83906 FINISHED
Object Chinese culture 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: Chinese culture | Statement: [Wenzhong, honorsCulture, Chinese culture]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: honorsCulture
Context triple: [Wenzhong, honorsCulture, Chinese culture]
  • A. cultHonors
    Indicates that a cult pays reverence, worship, or special honor to a particular figure, object, or concept.
  • B. honorsCategory
    Indicates that one entity is recognized or classified as belonging to a particular honors-related category defined by the other entity.
  • C. cultureHeroIn
    Indicates that an entity serves as a culture hero within a specified cultural or mythological tradition.
  • D. culturalCategory
    Indicates that one entity classifies or groups another entity according to a particular culture, tradition, or culturally defined type.
  • E. culturalElements chosen
    Indicates a relationship where certain elements (such as practices, symbols, or artifacts) belong to, express, or characterize a particular culture or cultural context.
  • 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_69f01d8328c48190bc0e5f9b9b848582 completed April 28, 2026, 2:37 a.m.
NER Named-entity recognition batch_69f6aaf50be08190a2b62a6d881f8aee completed May 3, 2026, 1:55 a.m.
PD Predicate disambiguation batch_69f6aa1c555081908787dbf76147f180 completed May 3, 2026, 1:51 a.m.
Created at: April 28, 2026, 4:37 a.m.