Triple

T24811032
Position Surface form Disambiguated ID Type / Status
Subject Mueller calculus E620786 entity
Predicate classificationOfSystems P6736 FINISHED
Object depolarizing Mueller matrices 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: depolarizing Mueller matrices | Statement: [Mueller calculus, classificationOfSystems, depolarizing Mueller matrices]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: classificationOfSystems
Context triple: [Mueller calculus, classificationOfSystems, depolarizing Mueller matrices]
  • A. classificationSystem chosen
    Indicates a relationship where an entity is organized or categorized according to a particular classification scheme or taxonomy.
  • B. classificationSystemBasedOn
    Indicates that one classification system is organized, defined, or derived using another classification system as its basis or reference framework.
  • C. classificationSystemName
    Indicates the name or label assigned to a particular classification system used to categorize or organize entities.
  • D. definesClassification
    Indicates that one entity specifies or establishes the classification or category to which another entity belongs.
  • E. modelsSystemsWith
    Indicates that one entity creates or uses a representation or abstraction to describe, analyze, or simulate another system.
  • 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_69e2fabf26bc8190b191faac8f67065b completed April 18, 2026, 3:30 a.m.
NER Named-entity recognition batch_69f44a417a58819081777e18dda149fd completed May 1, 2026, 6:37 a.m.
PD Predicate disambiguation batch_69f442a977b08190b44eac040cb90211 completed May 1, 2026, 6:05 a.m.
Created at: April 18, 2026, 4:50 a.m.