Triple

T1495509
Position Surface form Disambiguated ID Type / Status
Subject Mexican Plateau E29675 entity
Predicate majorCity P316 FINISHED
Object León E217591 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: [Mexican Plateau, majorCity, León]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: León
Context triple: [Mexican Plateau, majorCity, León]
  • A. León
    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 chosen
    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_69a498dba1d8819093b46a3a8d2485f1 completed March 1, 2026, 7:51 p.m.
NER Named-entity recognition batch_69a4c6ec70c48190a94f6e1002848eae completed March 1, 2026, 11:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69ae1fb455888190a1408a25b93a70ce completed March 9, 2026, 1:17 a.m.
Created at: March 1, 2026, 8:12 p.m.