Triple

T6056924
Position Surface form Disambiguated ID Type / Status
Subject King of León E134936 entity
Predicate hasCapital P204 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: [King of León, hasCapital, León]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: León
Context triple: [King of León, hasCapital, 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. León
    León is a major industrial and commercial city in central Mexico, renowned especially for its leather and footwear production.
  • E. Ávila
    Ávila is a historic walled city in central Spain, renowned for its remarkably well-preserved medieval fortifications and Romanesque and Gothic architecture.
  • 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_69c00877b6d4819096b0e163728b73a3 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c0570bf01c8190a8b2c25b7805d403 completed March 22, 2026, 8:54 p.m.
NED1 Entity disambiguation (via context triple) batch_69c11d0e06288190b4389b43825d5929 completed March 23, 2026, 10:59 a.m.
Created at: March 22, 2026, 4:09 p.m.