Triple

T13556262
Position Surface form Disambiguated ID Type / Status
Subject Peace dollar E323781 entity
Predicate reverseDesignElement P110337 FINISHED
Object rays of the sun 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: rays of the sun | Statement: [Peace dollar, reverseDesignElement, rays of the sun]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: reverseDesignElement
Context triple: [Peace dollar, reverseDesignElement, rays of the sun]
  • A. reverseDesigns
    Indicates that one entity creates or specifies designs that are the reverse or inverse configuration of another entity’s designs.
  • B. reverseDesignSubject
    Indicates that the subject is the entity for which a design or plan is derived by reversing or backtracking from an existing outcome or artifact.
  • C. reverseDesigner
    Indicates that one entity is the designer or creator of another entity, with the direction of the relationship reversed from a primary “designer” predicate.
  • D. reverseFeature
    Indicates that one feature is the inverse or opposite counterpart of another feature in a given context.
  • E. pairedWithReverseDesign
    Indicates that an entity is associated with another entity that represents its reverse or opposite design counterpart.
  • 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_69d8076830b48190910a902bae5888e2 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbbb9ee3f081909056dc1a92c40b7a completed April 12, 2026, 3:34 p.m.
PD Predicate disambiguation batch_69dbae13bec4819084c1770638c00ed9 completed April 12, 2026, 2:37 p.m.
PDg Predicate description generation batch_69dbbb8c77dc8190b7bd803b5e168d23 completed April 12, 2026, 3:34 p.m.
Created at: April 9, 2026, 9:47 p.m.