Triple

T19367002
Position Surface form Disambiguated ID Type / Status
Subject Northwestern Ohio E484428 entity
Predicate includesCity P3207 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: [Northwestern Ohio, includesCity, Toledo, Ohio]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toledo, Ohio
Context triple: [Northwestern Ohio, includesCity, 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_69d8e8d305088190ad13571532aa454c completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e619ac26d4819095836d737b629cf1 completed April 20, 2026, 12:18 p.m.
Created at: April 10, 2026, 1:35 p.m.