Triple

T8192239
Position Surface form Disambiguated ID Type / Status
Subject Province of Toledo E191338 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: [Province of Toledo, capital, Toledo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toledo
Context triple: [Province of Toledo, 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. 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.
  • D. Columbus
    Columbus is a city in eastern Mississippi known for its historic architecture, role in the American Civil War, and as part of the Golden Triangle region.
  • E. Columbus
    Columbus is a common Italian-origin surname most famously associated with the explorer Christopher Columbus and his descendants.
  • 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_69ca82c5b6948190a583c096fb0a6c71 completed March 30, 2026, 2:03 p.m.
NER Named-entity recognition batch_69cb4da4a6f08190be8088a28d928341 completed March 31, 2026, 4:29 a.m.
NED1 Entity disambiguation (via context triple) batch_69cceda1b22c8190acc1a2cd0fe36b70 completed April 1, 2026, 10:04 a.m.
Created at: March 30, 2026, 5:42 p.m.