Triple

T15879908
Position Surface form Disambiguated ID Type / Status
Subject Muñecas Province E385048 entity
Predicate partOf P40 FINISHED
Object La Paz Department E61179 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: La Paz Department | Statement: [Muñecas Province, partOf, La Paz Department]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: La Paz Department
Context triple: [Muñecas Province, partOf, La Paz Department]
  • A. La Paz Department chosen
    La Paz Department is a highland administrative region in western Bolivia that includes the city of La Paz and encompasses part of the Lake Titicaca basin in the Andes.
  • B. La Paz Department
    La Paz Department is an administrative region in central El Salvador that includes part of the country’s Pacific coastline and hosts its main international airport.
  • C. Cochabamba Department
    Cochabamba Department is a central Bolivian administrative region known for its fertile valleys, temperate climate, and the city of Cochabamba as its capital.
  • D. Tarija Department
    Tarija Department is an administrative region in southern Bolivia known for its wine production, mild climate, and the city of Tarija as its capital.
  • E. San Miguel Department
    San Miguel Department is an administrative division in eastern El Salvador that includes the city of San Miguel as its capital and economic center.
  • 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_69d86da4e86481909f1325fdc971b5ec completed April 10, 2026, 3:25 a.m.
NER Named-entity recognition batch_69e15600863c8190a2dbfd6d7ff495d7 completed April 16, 2026, 9:34 p.m.
NED1 Entity disambiguation (via context triple) batch_69ffa9529ac48190993d1af234faea3b completed May 9, 2026, 9:38 p.m.
Created at: April 10, 2026, 4:51 a.m.