Triple

T20027119
Position Surface form Disambiguated ID Type / Status
Subject Carazo E495012 entity
Predicate borders P224 FINISHED
Object Masaya Department NE NERFINISHED

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: Masaya Department | Statement: [Carazo, borders, Masaya Department]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Masaya Department
Context triple: [Carazo, borders, Masaya Department]
  • A. Masaya Department chosen
    Masaya Department is an administrative region in western Nicaragua known for its active Masaya Volcano, traditional handicrafts, and cultural festivals.
  • B. Matagalpa Department
    Matagalpa Department is a highland region in north-central Nicaragua known for its coffee production, cool climate, and mountainous landscapes.
  • C. Boaco Department
    Boaco Department is an inland administrative region of central Nicaragua known for its hilly terrain, cattle ranching, and agricultural economy.
  • D. Managua Department
    Managua Department is an administrative region of Nicaragua that includes the nation’s capital city, Managua, and serves as its political and economic center.
  • E. Olancho Department
    Olancho Department is the largest and one of the most sparsely populated administrative regions of Honduras, known for its extensive ranching lands, forests, and agricultural production.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69da626bfd288190aa5d65098b6433ae completed April 11, 2026, 3:02 p.m.
NER Named-entity recognition batch_69e6628e1eec81908e4c9b2b0b68f0e4 completed April 20, 2026, 5:29 p.m.
Created at: April 11, 2026, 3:35 p.m.