Triple

T2581206
Position Surface form Disambiguated ID Type / Status
Subject Capital University E57094 entity
Predicate locatedIn P40 FINISHED
Object Bexley, Ohio E312778 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: Bexley, Ohio | Statement: [Capital University, locatedIn, Bexley, Ohio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bexley, Ohio
Context triple: [Capital University, locatedIn, Bexley, Ohio]
  • A. Bexley, Ohio chosen
    Bexley, Ohio is a small, affluent suburban city near downtown Columbus known for its historic homes, tree-lined streets, and institutions like Capital University.
  • B. Bellevue, Ohio
    Bellevue, Ohio is a small city in north-central Ohio known for its railroad heritage and location spanning multiple counties.
  • C. Bryan, Ohio
    Bryan, Ohio is a small city in northwestern Ohio that serves as the county seat of Williams County.
  • D. Englewood, Ohio
    Englewood, Ohio is a suburban city in Montgomery County that forms part of the Dayton metropolitan area in southwestern Ohio.
  • E. Xenia, Ohio
    Xenia, Ohio is a small city in southwestern Ohio known for its historic downtown, proximity to Dayton, and extensive network of bike trails.
  • 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_69ab4a4dca6481908c301f8e317396e7 completed March 6, 2026, 9:42 p.m.
NER Named-entity recognition batch_69abd3c6da888190ba7abfe37d182602 completed March 7, 2026, 7:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69b12df6ad908190b0b484b6fd82ffb5 completed March 11, 2026, 8:55 a.m.
Created at: March 6, 2026, 9:49 p.m.