Triple

T17845717
Position Surface form Disambiguated ID Type / Status
Subject Grayling, Michigan E445652 entity
Predicate hasEducationalInstitution P113 FINISHED
Object Grayling High School NE NERFINISHED

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: Grayling High School | Statement: [Grayling, Michigan, hasEducationalInstitution, Grayling High School]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Grayling High School
Context triple: [Grayling, Michigan, hasEducationalInstitution, Grayling High School]
  • A. Grayling High School chosen
    Grayling High School is the primary public secondary school serving students in the small northern Michigan community of Grayling.
  • B. Grant High School
    Grant High School is a secondary school that serves students from the Grant Park area.
  • C. Forest High School
    Forest High School is a secondary school located in Cinderford, Gloucestershire, England.
  • D. Hall High School
    Hall High School is a public secondary school serving students in the West Hartford, Connecticut area.
  • E. Greenfield High School
    Greenfield High School is a public secondary school serving students in the city of Greenfield in western Massachusetts.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8b9f26f18819089c9e43250bee6ae completed April 10, 2026, 8:50 a.m.
NER Named-entity recognition batch_69e48ffa4c648190a88a4b0733493d91 completed April 19, 2026, 8:19 a.m.
Created at: April 10, 2026, 10:16 a.m.