Triple

T23354276
Position Surface form Disambiguated ID Type / Status
Subject Calle de Toledo (Madrid) E593001 entity
Predicate namedAfter P63 FINISHED
Object city of Toledo 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: city of Toledo | Statement: [Calle de Toledo (Madrid), namedAfter, city of Toledo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: city of Toledo
Context triple: [Calle de Toledo (Madrid), namedAfter, 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 small village in east-central Illinois that serves as the administrative and commercial hub of Cumberland County.
  • C. Toledo chosen
    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.
  • D. Toledo
    Toledo is a Spanish-origin surname borne by various notable individuals across fields such as sports, politics, and the arts.
  • E. Toledo
    Toledo is a major city in northwestern Ohio, known as an industrial and transportation hub on the western end of Lake Erie.
  • 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_69e25d24d2a4819092e6ede74c2a918d completed April 17, 2026, 4:17 p.m.
NER Named-entity recognition batch_69f19a169bb88190a2ca659fce1133e5 completed April 29, 2026, 5:41 a.m.
Created at: April 17, 2026, 5:20 p.m.