Triple

T3975143
Position Surface form Disambiguated ID Type / Status
Subject Poás E85620 entity
Predicate nearCity P350 FINISHED
Object Alajuela E321025 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: Alajuela | Statement: [Poás, nearCity, Alajuela]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Alajuela
Context triple: [Poás, nearCity, Alajuela]
  • A. Alajuela Province chosen
    Alajuela Province is a region in north-central Costa Rica known for its agricultural production, volcanic landscapes, and popular ecotourism destinations.
  • B. San José de las Lajas
    San José de las Lajas is a Cuban city that serves as the capital of Mayabeque Province and an important agricultural and industrial center near Havana.
  • C. Guatemala City
    Guatemala City is the capital and largest city of Guatemala, serving as the country’s political, economic, and cultural center.
  • D. San Pedro Sula
    San Pedro Sula is a large industrial and commercial city in northern Honduras, historically known as the country’s economic hub.
  • E. Juigalpa
    Juigalpa is a city in central Nicaragua that serves as the capital of the Chontales Department and a regional hub for agriculture and cattle ranching.
  • 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_69aed93908348190a26c8aaf4fab3e86 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aef9b511f88190afca12c77481b344 completed March 9, 2026, 4:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69b54c472d048190843b29a6a9a4be86 completed March 14, 2026, 11:53 a.m.
Created at: March 9, 2026, 3:33 p.m.