Triple

T7452008
Position Surface form Disambiguated ID Type / Status
Subject Schottenstein Center E172029 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: [Schottenstein Center, city, Columbus]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Columbus
Context triple: [Schottenstein Center, city, Columbus]
  • A. 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.
  • B. 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.
  • C. Columbus
    Columbus is the cautious, rule-obsessed protagonist and narrator of the post-apocalyptic comedy film "Zombieland."
  • D. Columbus
    Columbus is a common Italian-origin surname most famously associated with the explorer Christopher Columbus and his descendants.
  • 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_69c68a66554c8190add75c65942c0317 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f38d6a8c8190af2e73c719da87a6 completed March 27, 2026, 9:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69cfd04f80fc8190aae7c4823ddecb4a completed April 3, 2026, 2:35 p.m.
Created at: March 27, 2026, 3:14 p.m.