Triple

T10164239
Position Surface form Disambiguated ID Type / Status
Subject Leovigild E233966 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: [Leovigild, capital, Toledo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toledo
Context triple: [Leovigild, capital, Toledo]
  • A. Toledo
    Toledo is a major city in northwestern Ohio, known as an industrial and transportation hub on the western end of Lake Erie.
  • B. 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.
  • 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 major city in western Georgia located on the Chattahoochee River, known for its military base Fort Moore (formerly Fort Benning) and its role as a regional economic and cultural center.
  • 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_69ca848e80748190b91d1e04d35512c7 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cdec6a7bb48190952f4318af9cc32b completed April 2, 2026, 4:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69d354fc0a808190aa57b68708d91590 completed April 6, 2026, 6:38 a.m.
Created at: March 30, 2026, 9:09 p.m.