Triple

T35158287
Position Surface form Disambiguated ID Type / Status
Subject Doshisha schools E1015187 entity
Predicate educationalLevelCoverage P97458 FINISHED
Object kindergarten to university 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: kindergarten to university | Statement: [Doshisha schools, educationalLevelCoverage, kindergarten to university]
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: educationalLevelCoverage
Context triple: [Doshisha schools, educationalLevelCoverage, kindergarten to university]
  • A. educationLevelsCovered chosen
    Indicates the range or specific levels of education that are included or addressed by something (such as a program, policy, or resource).
  • B. educationLevelCharacteristic
    Indicates that one entity specifies, describes, or constrains the education level associated with another entity.
  • C. governsLevelOfEducation
    Indicates that one entity has authority or control over determining the level or standard of education provided to another entity.
  • D. educationStatus
    Indicates the current or achieved level, stage, or condition of an entity’s formal education.
  • E. educationType
    Indicates the specific category or level of education associated with an entity, such as formal, informal, primary, secondary, or higher education.
  • 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_69f76ddb3a708190b521ba2970b17178 completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f78cf6d1148190881980c8c2ce7b7d completed May 3, 2026, 5:59 p.m.
PD Predicate disambiguation batch_69f78b9106008190930b3b3675b737d6 completed May 3, 2026, 5:53 p.m.
Created at: May 3, 2026, 4:02 p.m.