Triple

T32180478
Position Surface form Disambiguated ID Type / Status
Subject Dictee E821964 entity
Predicate sectionalFramework P173828 FINISHED
Object modeled on the Greek muses 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: modeled on the Greek muses | Statement: [Dictee, sectionalFramework, modeled on the Greek muses]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: sectionalFramework
Context triple: [Dictee, sectionalFramework, modeled on the Greek muses]
  • A. frameworkWithin
    Indicates that one framework is contained, defined, or operates conceptually within the scope or structure of another framework.
  • B. sectionFunction
    Indicates the functional role or purpose that a particular section serves within a larger structure or context.
  • C. frameworkFor
    Indicates that one entity serves as a supporting structure, system, or basis that organizes, guides, or enables the development or functioning of another entity.
  • D. frameworkLayer
    Indicates a relationship where one framework is organized within, built upon, or conceptually assigned to a particular architectural or conceptual layer.
  • E. section
    Indicates that one entity is a distinct part, division, or segment of another entity within a larger whole.
  • 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_69f3490755288190aee11740a34862f9 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6ba7cbc708190ab91b828e5ef2976 completed May 3, 2026, 3:01 a.m.
PD Predicate disambiguation batch_69f6b6293188819080d5041ca0adb969 completed May 3, 2026, 2:42 a.m.
PDg Predicate description generation batch_69f6b960ca4081909a77690c2b122f5e completed May 3, 2026, 2:56 a.m.
Created at: May 1, 2026, 12:34 a.m.