Triple

T11584534
Position Surface form Disambiguated ID Type / Status
Subject Taifa of Toledo E274717 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: [Taifa of Toledo, capital, Toledo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Toledo
Context triple: [Taifa 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 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 city in eastern Mississippi known for its historic architecture, role in the American Civil War, and as part of the Golden Triangle region.
  • 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_69d6aae6b14c81908dc5a74bad7591f9 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8904db5748190ae5f10ae86ccdf46 completed April 10, 2026, 5:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef1307da188190918d0f50b2fd37fa completed April 27, 2026, 7:40 a.m.
Created at: April 8, 2026, 9:38 p.m.