Triple

T8259807
Position Surface form Disambiguated ID Type / Status
Subject Socrates and Polus E193164 entity
Predicate contrastsViewOf P32726 FINISHED
Object rhetoric as flattery versus rhetoric as a craft 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: rhetoric as flattery versus rhetoric as a craft | Statement: [Socrates and Polus, contrastsViewOf, rhetoric as flattery versus rhetoric as a craft]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: contrastsViewOf
Context triple: [Socrates and Polus, contrastsViewOf, rhetoric as flattery versus rhetoric as a craft]
  • A. exploresContrastBetween chosen
    Indicates a relationship in which one entity examines, highlights, or analyzes the differences or oppositions between two or more entities, ideas, or situations.
  • B. achievesContrast
    Indicates that one entity creates or enhances a visual or conceptual difference relative to another entity.
  • C. viewOver
    Indicates that one entity has a visual perspective overlooking or facing another entity, typically providing a vantage point onto it.
  • D. expressesViewOn
    Indicates that one entity communicates or holds an opinion, stance, or perspective regarding another entity or topic.
  • E. viewOnAnalogy
    Indicates a relationship where one entity interprets, understands, or evaluates another entity by drawing an analogy to something else.
  • 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_69ca82dfad9c8190b8cd18fb89f50f40 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb793479d08190bd0dd8740bebff95 completed March 31, 2026, 7:35 a.m.
PD Predicate disambiguation batch_69cb36b6d5548190b665a6cce14c69f7 completed March 31, 2026, 2:51 a.m.
Created at: March 30, 2026, 5:49 p.m.