Triple

T376222
Position Surface form Disambiguated ID Type / Status
Subject Crown of Castile E8378 entity
Predicate capital P234 FINISHED
Object Toledo E12295 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 | Statement: [Crown of Castile, capital, Toledo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toledo
Context triple: [Crown of Castile, capital, Toledo]
  • A. 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.
  • B. Toledo
    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. Akron
    Akron is an industrial city in northeastern Ohio known historically for its rubber and tire manufacturing industry.
  • E. Youngstown
    Youngstown is an industrial city in northeastern Ohio historically known for its steel production and central role in the Rust Belt’s economic rise and decline.
  • 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_69a2e7f2ec648190b42bc7db424f8109 completed Feb. 28, 2026, 1:04 p.m.
NER Named-entity recognition batch_69a2ec169a848190a577aa093c878839 completed Feb. 28, 2026, 1:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69a3f4dd9a1c8190a0fc7012a24425c4 completed March 1, 2026, 8:12 a.m.
Created at: Feb. 28, 2026, 1:08 p.m.