Triple

T21658721
Position Surface form Disambiguated ID Type / Status
Subject San Miguelito E534536 entity
Predicate countryCapital P204 FINISHED
Object Tegucigalpa 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: Tegucigalpa | Statement: [San Miguelito, countryCapital, Tegucigalpa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tegucigalpa
Context triple: [San Miguelito, countryCapital, Tegucigalpa]
  • A. Tegucigalpa chosen
    Tegucigalpa is the capital and largest city of Honduras, serving as its political, cultural, and economic center.
  • B. San Pedro Sula
    San Pedro Sula is a large industrial and commercial city in northern Honduras, historically known as the country’s economic hub.
  • C. San José de Comayagua
    San José de Comayagua is a municipality and town located in the central Honduran highlands within the Comayagua Department.
  • D. San Salvador
    San Salvador is the largest city of El Salvador and its political, cultural, and economic center.
  • E. Santiago de los Caballeros
    Santiago de los Caballeros is the second-largest city in the Dominican Republic, known as a major cultural, economic, and historical center in the Cibao region.
  • 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_69e0c467e1f48190af2650b19175abc4 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69ef6c05a8d881909f747635bdb4ef09 completed April 27, 2026, 2 p.m.
Created at: April 16, 2026, 6:36 p.m.