Triple

T10709128
Position Surface form Disambiguated ID Type / Status
Subject Fisher College of Business E252486 entity
Predicate city P40 FINISHED
Object Columbus 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 | Statement: [Fisher College of Business, city, Columbus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Columbus
Context triple: [Fisher College of Business, city, Columbus]
  • A. Columbus
    Columbus is a city in eastern Mississippi known for its historic architecture, role in the American Civil War, and as part of the Golden Triangle region.
  • B. Columbus
    Columbus is a major city in western Georgia located on the Chattahoochee River, known for its military base Fort Moore (formerly Fort Benning) and its role as a regional economic and cultural center.
  • C. Columbus
    Columbus is a common Italian-origin surname most famously associated with the explorer Christopher Columbus and his descendants.
  • D. Columbus
    Columbus is the cautious, rule-obsessed protagonist and narrator of the post-apocalyptic comedy film "Zombieland."
  • E. 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.
  • 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_69d6aa5cbabc8190973e683950d89faf completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fe5063bc8190ba12fd68a59c9a03 completed April 9, 2026, 1:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69e3e6afdf0c8190924cb14512a89ee8 completed April 18, 2026, 8:16 p.m.
Created at: April 8, 2026, 9:13 p.m.