Triple

T16410061
Position Surface form Disambiguated ID Type / Status
Subject Whitehall, Ohio E398537 entity
Predicate borders P224 FINISHED
Object Columbus, Ohio E9221 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: Columbus, Ohio | Statement: [Whitehall, Ohio, borders, Columbus, Ohio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Columbus, Ohio
Context triple: [Whitehall, Ohio, borders, Columbus, Ohio]
  • A. Columbus, Ohio chosen
    Columbus, Ohio is the capital and largest city of Ohio, known for its diverse economy, major universities, and role as a cultural and political center in the region.
  • B. Hamilton, Ohio
    Hamilton, Ohio is a historic industrial city in southwestern Ohio that serves as the county seat of Butler County and is part of the greater Cincinnati–Miami Valley region.
  • C. Columbus
    Columbus is the cautious, rule-obsessed protagonist and narrator of the post-apocalyptic comedy film "Zombieland."
  • D. Columbus
    Columbus is the European Space Agency’s research laboratory module attached to the International Space Station, used for a wide range of scientific experiments in microgravity.
  • E. Columbus
    Columbus is the capital and largest city of Ohio, known for its diverse economy, major universities, and vibrant arts and sports scenes.
  • 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_69d87f2950248190bc8ad9b9bebdc8c8 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e328731a408190b38dcab0b7bb65ff completed April 18, 2026, 6:45 a.m.
NED1 Entity disambiguation (via context triple) batch_6a008a2156008190a079c9f1b721d40a completed May 10, 2026, 1:37 p.m.
Created at: April 10, 2026, 5:09 a.m.