Triple

T1475255
Position Surface form Disambiguated ID Type / Status
Subject Lucille E30825 entity
Predicate narrativeLocation P40 FINISHED
Object Toledo, Ohio E25661 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: Toledo, Ohio | Statement: [Lucille, narrativeLocation, Toledo, Ohio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toledo, Ohio
Context triple: [Lucille, narrativeLocation, Toledo, Ohio]
  • A. Toledo
    Toledo is a historic Spanish city renowned for its medieval architecture, cultural heritage, and role as a major political and religious center in Spain’s history.
  • B. Toledo chosen
    Toledo is a major city in northwestern Ohio, known as an industrial and transportation hub on the western end of Lake Erie.
  • C. Columbus, Ohio
    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.
  • D. Canton, Ohio
    Canton, Ohio is a mid-sized city in northeastern Ohio known for its industrial heritage and as the home of the Pro Football Hall of Fame.
  • E. Marietta, Ohio
    Marietta, Ohio is a historic city in southeastern Ohio known as the first permanent settlement of the Northwest Territory, located along the Ohio and Muskingum Rivers.
  • 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_69a498fe55a88190ab7f9e40ace88e49 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c602387c8190b97a20c8e05e3d16 completed March 1, 2026, 11:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad2940a44c8190967a62781cca0306 completed March 8, 2026, 7:46 a.m.
Created at: March 1, 2026, 8:11 p.m.