Triple

T8957091
Position Surface form Disambiguated ID Type / Status
Subject Toledo, Oregon E213499 entity
Predicate hasMunicipalGovernment P3291 FINISHED
Object City of Toledo 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: City of Toledo | Statement: [Toledo, Oregon, hasMunicipalGovernment, City of Toledo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: City of Toledo
Context triple: [Toledo, Oregon, hasMunicipalGovernment, City of Toledo]
  • A. 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.
  • 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. Ohio City
    Ohio City is a historic and revitalized neighborhood on Cleveland’s near west side, known for its vibrant dining scene, craft breweries, and cultural landmarks.
  • E. The Glass City
    The Glass City is a nickname commonly used for cities known for their prominent glass industry, architecture, or reflective skylines, such as Toledo, Ohio.
  • 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_69ca8399ad2081909f8fa41d4314c215 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc6728965881908e9f14aaee0c5a18 completed April 1, 2026, 12:30 a.m.
NED1 Entity disambiguation (via context triple) batch_69cfd09e378c8190bb9f5d78a3b91fe7 completed April 3, 2026, 2:37 p.m.
Created at: March 30, 2026, 7 p.m.