Triple

T9692666
Position Surface form Disambiguated ID Type / Status
Subject Simuwu Ding E234570 entity
Predicate importanceInIconography P89653 FINISHED
Object benchmark example of Shang taotie design 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: benchmark example of Shang taotie design | Statement: [Simuwu Ding, importanceInIconography, benchmark example of Shang taotie design]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: importanceInIconography
Context triple: [Simuwu Ding, importanceInIconography, benchmark example of Shang taotie design]
  • A. iconographicFunction
    Indicates the symbolic or representational role that something serves within an image or visual composition.
  • B. iconographyInfluence
    Indicates that one entity’s visual symbols, motifs, or stylistic elements have shaped or informed the iconographic style or imagery of another entity.
  • C. iconographyType
    Indicates the specific kind or category of visual symbolism or imagery used to represent something.
  • D. iconographyFeature
    Indicates a visual element or motif that appears as a distinct feature within a work’s iconography.
  • E. iconographicCategory
    Indicates the classification of an entity based on the type or theme of its visual or symbolic representation.
  • 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_69ca84ca73208190957a900c8543bdcc completed March 30, 2026, 2:12 p.m.
NER Named-entity recognition batch_69cd9d0727908190897894151c0ee7c2 completed April 1, 2026, 10:32 p.m.
PD Predicate disambiguation batch_69ccd5b840f081909f66bf0b66d17d9b completed April 1, 2026, 8:22 a.m.
PDg Predicate description generation batch_69ccd9408c848190b84dd74d87f76273 completed April 1, 2026, 8:37 a.m.
Created at: March 30, 2026, 8:17 p.m.