Triple

T2432648
Position Surface form Disambiguated ID Type / Status
Subject Chicago Public Schools E52880 entity
Predicate appliesEducationalSystem P340 FINISHED
Object K–12 education 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: K–12 education | Statement: [Chicago Public Schools, appliesEducationalSystem, K–12 education]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: appliesEducationalSystem
Context triple: [Chicago Public Schools, appliesEducationalSystem, K–12 education]
  • A. educationSystem chosen
    Indicates the relationship in which an entity is part of, governed by, or operates within a particular system or structure of education.
  • B. introducedEducationSystem
    Indicates that an entity established or brought a particular education system into use for another entity or context.
  • C. educationSystemCharacteristic
    Indicates a characteristic, feature, or attribute that describes an education system.
  • D. educationalModel
    Indicates that one entity serves as an educational model, framework, or paradigm that guides or structures the teaching, learning, or training practices of another entity.
  • E. schoolSystemType
    Indicates the classification or organizational model of a school system (e.g., public, private, charter, or other structural type).
  • 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_69ab4959bcc0819083246f9fb10439e3 completed March 6, 2026, 9:38 p.m.
NER Named-entity recognition batch_69abcc74a5108190a3a9631b0cc1a127 completed March 7, 2026, 6:57 a.m.
PD Predicate disambiguation batch_69abc5aa1b60819081b87f7985c6cff3 completed March 7, 2026, 6:28 a.m.
Created at: March 6, 2026, 9:43 p.m.