Triple

T5718825
Position Surface form Disambiguated ID Type / Status
Subject Lago Xolotlán E126088 entity
Predicate hasNearbyCity P350 FINISHED
Object León E143424 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: [Lago Xolotlán, hasNearbyCity, León]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: León
Context triple: [Lago Xolotlán, hasNearbyCity, 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 chosen
    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_69c0082e3d548190950169847b43043b completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c024e1ec7c8190a08e1b7954db2a9d completed March 22, 2026, 5:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0bf8fc8b881908c600c2f7de0d691 completed March 23, 2026, 4:20 a.m.
Created at: March 22, 2026, 3:46 p.m.