Triple

T16337403
Position Surface form Disambiguated ID Type / Status
Subject Southern Cuba E396711 entity
Predicate containsCity P294 FINISHED
Object Bayamo E130090 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: Bayamo | Statement: [Southern Cuba, containsCity, Bayamo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bayamo
Context triple: [Southern Cuba, containsCity, Bayamo]
  • A. Bayamo chosen
    Bayamo is one of Cuba’s oldest colonial cities, historically significant as an early Spanish settlement and a center of Cuban independence sentiment.
  • B. Jarabacoa
    Jarabacoa is a mountainous town in the Dominican Republic known for its cool climate, rivers, and outdoor adventure tourism.
  • C. Aguas Buenas
    Aguas Buenas is a mountainous municipality in central Puerto Rico known for its cool climate, caves, and scenic rural landscapes.
  • D. San Juan de la Maguana
    San Juan de la Maguana is a historic city in the western Dominican Republic known as a regional agricultural center and gateway to the country’s central mountain range.
  • E. Guanabacoa
    Guanabacoa is a historic municipality of Havana, Cuba, known for its colonial heritage and strong Afro-Cuban religious and cultural traditions.
  • 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_69d87f26864c819088365ca381a003c2 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e2c4e524448190870a6ef569017b56 completed April 17, 2026, 11:40 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0026193a3c81909c640426ab798c1c completed May 10, 2026, 6:30 a.m.
Created at: April 10, 2026, 5:07 a.m.