Triple

T1992445
Position Surface form Disambiguated ID Type / Status
Subject Kingdom of León E43280 entity
Predicate capital P234 FINISHED
Object León E49458 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: León | Statement: [Kingdom of León, capital, León]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: León
Context triple: [Kingdom of León, capital, León]
  • A. León chosen
    León is a historic city and former kingdom in northwestern Spain, renowned for its medieval architecture and significant role in the formation of the Spanish state.
  • B. León
    León is a historic city in western Nicaragua known for its colonial architecture, vibrant cultural life, and role as an intellectual and political center of the country.
  • C. León
    León is a historic and successful Mexican professional football club known for its multiple Liga MX titles and passionate fan base.
  • D. Ávila
    Ávila is a historic walled city in central Spain, renowned for its remarkably well-preserved medieval fortifications and Romanesque and Gothic architecture.
  • E. Burgos
    Burgos is a historic city in northern Spain known for its medieval architecture and its prominent role during the Spanish Civil War.
  • 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_69a88714cf2c819081644be450b8356e completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abb846f1c0819081edd8d5eb59adce completed March 7, 2026, 5:31 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae5179b3348190bfec5530baf4ca86 completed March 9, 2026, 4:50 a.m.
Created at: March 4, 2026, 7:37 p.m.