Triple

T5703873
Position Surface form Disambiguated ID Type / Status
Subject Kent State shootings E125735 entity
Predicate city P40 FINISHED
Object Kent, Ohio E156899 NE 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: Kent, Ohio | Statement: [Kent State shootings, city, Kent, Ohio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kent, Ohio
Context triple: [Kent State shootings, city, Kent, Ohio]
  • A. Kent, Ohio chosen
    Kent, Ohio is a city in northeastern Ohio best known as the home of Kent State University.
  • B. Kettering, Ohio
    Kettering, Ohio is a suburban city near Dayton known for its residential communities, parks, and role as a commercial and cultural hub in the Miami Valley region.
  • C. Oakland, Kentucky
    Oakland, Kentucky is a small town in Warren County that functions as part of the broader Bowling Green regional community in south-central Kentucky.
  • D. Bryan, Ohio
    Bryan, Ohio is a small city in northwestern Ohio that serves as the county seat of Williams County.
  • E. Montgomery, Ohio
    Montgomery, Ohio is a suburban city in Hamilton County near Cincinnati, known for its historic charm, affluent residential character, and well-regarded schools.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69c0082c96988190b3a6a201edce472a completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c024585d14819098ec34fd5a858836 completed March 22, 2026, 5:18 p.m.
NED1 Entity disambiguation (via context triple) batch_69c24381aff48190980ada94ee95593e completed March 24, 2026, 7:55 a.m.
Created at: March 22, 2026, 3:45 p.m.