Triple

T5108548
Position Surface form Disambiguated ID Type / Status
Subject Anaximenes of Miletus E115157 entity
Predicate usedConcept P58359 FINISHED
Object quantitative change to explain qualitative differences 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: quantitative change to explain qualitative differences | Statement: [Anaximenes of Miletus, usedConcept, quantitative change to explain qualitative differences]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: usedConcept
Context triple: [Anaximenes of Miletus, usedConcept, quantitative change to explain qualitative differences]
  • A. usedInConcept chosen
    Indicates that something (such as a method, idea, or component) is employed as part of, or plays a role within, a particular concept.
  • B. featuredConcept
    Indicates that one concept is highlighted or given special prominence relative to others in a particular context.
  • C. introducedConcept
    Indicates that one entity is responsible for presenting, defining, or bringing a new concept into use or awareness for another entity or context.
  • D. hasConcept
    Indicates that an entity includes, embodies, or is associated with a particular concept.
  • E. usedTerm
    Indicates that one entity employed, referenced, or applied a particular term in some 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_69bd4440b3348190be1251fd8b7951f1 completed March 20, 2026, 12:57 p.m.
NER Named-entity recognition batch_69bd75aa6b088190b02cdb66ec4a11f0 completed March 20, 2026, 4:28 p.m.
PD Predicate disambiguation batch_69bd715fe3a8819087d3065adddba515 completed March 20, 2026, 4:10 p.m.
Created at: March 20, 2026, 1:41 p.m.