Triple

T21153672
Position Surface form Disambiguated ID Type / Status
Subject Willys-Overland Motors E521256 entity
Predicate basedIn P40 FINISHED
Object Toledo, Ohio NE NERFINISHED

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: [Willys-Overland Motors, basedIn, Toledo, Ohio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toledo, Ohio
Context triple: [Willys-Overland Motors, basedIn, Toledo, Ohio]
  • A. Toledo
    Toledo is a Spanish-origin surname borne by various notable individuals across fields such as sports, politics, and the arts.
  • B. 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.
  • C. Toledo chosen
    Toledo is a major city in northwestern Ohio, known as an industrial and transportation hub on the western end of Lake Erie.
  • D. Toledo
    Toledo is a small village in east-central Illinois that serves as the administrative and commercial hub of Cumberland County.
  • E. Toledo City
    Toledo City is a coastal component city on the western side of Cebu Island in the Philippines, known for its mining industry and port facilities.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b50d1ea481909c07e63c3ead9316 completed April 16, 2026, 10:08 a.m.
NER Named-entity recognition batch_69e7252929748190afd85be40294293f completed April 21, 2026, 7:20 a.m.
Created at: April 16, 2026, 2:58 p.m.