Triple

T17877902
Position Surface form Disambiguated ID Type / Status
Subject Mid-Michigan E447004 entity
Predicate containsCounty P5971 FINISHED
Object Isabella County 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: Isabella County | Statement: [Mid-Michigan, containsCounty, Isabella County]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Isabella County
Context triple: [Mid-Michigan, containsCounty, Isabella County]
  • A. Isabella County chosen
    Isabella County is a county in the U.S. state of Michigan, known for being home to the city of Mount Pleasant and Central Michigan University.
  • B. Pike County
    Pike County is a rural county in northeastern Pennsylvania known for its forests, rivers, and location along the Delaware River near the New York and New Jersey borders.
  • C. Pike County
    Pike County is a county in southeastern Alabama known for its agricultural economy and as the home of Troy University.
  • D. Pike County
    Pike County is a county in west-central Georgia, United States, known for its rural character and location within the Atlanta metropolitan area’s broader region.
  • E. Pike County
    Pike County is a rural county in southwestern Indiana known for its agricultural landscape, small communities, and proximity to coal mining and outdoor recreation areas.
  • 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_69d8b9f4c22c819093c2680434472894 completed April 10, 2026, 8:51 a.m.
NER Named-entity recognition batch_69e49c0c46108190b8edef2572b5ba90 completed April 19, 2026, 9:10 a.m.
Created at: April 10, 2026, 10:18 a.m.