Triple

T3968208
Position Surface form Disambiguated ID Type / Status
Subject Joint Task Force-Bravo E92265 entity
Predicate basedNear P350 FINISHED
Object Tegucigalpa E23093 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: Tegucigalpa | Statement: [Joint Task Force-Bravo, basedNear, Tegucigalpa]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tegucigalpa
Context triple: [Joint Task Force-Bravo, basedNear, 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 Salvador
    San Salvador is the largest city of El Salvador and its political, cultural, and economic center.
  • D. 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.
  • 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_69aed96624188190ac8c45bb57ab72b5 completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aef978a14c8190a7982a2e4489b6ea completed March 9, 2026, 4:46 p.m.
NED1 Entity disambiguation (via context triple) batch_69bd568effac81908bc52b5240e47c8c completed March 20, 2026, 2:15 p.m.
Created at: March 9, 2026, 3:32 p.m.