Triple

T2409305
Position Surface form Disambiguated ID Type / Status
Subject Franklin County, Ohio E50348 entity
Predicate contains P35 FINISHED
Object Reynoldsburg, Ohio E261066 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: Reynoldsburg, Ohio | Statement: [Franklin County, Ohio, contains, Reynoldsburg, Ohio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Reynoldsburg, Ohio
Context triple: [Franklin County, Ohio, contains, Reynoldsburg, Ohio]
  • A. Reynoldsburg, Ohio chosen
    Reynoldsburg, Ohio is a suburban city near Columbus best known as the longtime home of Victoria’s Secret’s corporate headquarters.
  • B. Miamisburg, Ohio
    Miamisburg, Ohio is a suburban city in southwestern Ohio known for its historic downtown and proximity to Dayton in the Miami Valley region.
  • C. Reading, Ohio
    Reading, Ohio is a small suburban city located just north of Cincinnati in Hamilton County.
  • D. Huber Heights, Ohio
    Huber Heights, Ohio is a suburban city in the Dayton metropolitan area known for its residential communities and location within the Miami Valley region.
  • E. Bryan, Ohio
    Bryan, Ohio is a small city in northwestern Ohio that serves as the county seat of Williams County.
  • 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_69a88b0339a88190a1207333cd271cc9 completed March 4, 2026, 7:41 p.m.
NER Named-entity recognition batch_69abc925c6e481909bfd45b361d21963 completed March 7, 2026, 6:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69af9060a6b88190b80e5fb0970957e1 completed March 10, 2026, 3:30 a.m.
Created at: March 4, 2026, 7:58 p.m.