Triple

T1617326
Position Surface form Disambiguated ID Type / Status
Subject La Paz E34749 entity
Predicate locatedIn 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: [La Paz, locatedIn, La Paz Department]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: La Paz Department
Context triple: [La Paz, locatedIn, 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. 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.
  • C. Sucre Department
    Sucre Department is an administrative region in northern Colombia, known for its Caribbean coastline, agricultural economy, and capital city Sincelejo.
  • D. Oruro Department
    Oruro Department is a high-altitude administrative region in western Bolivia known for its Andean landscapes, mining heritage, and vibrant Carnival of Oruro.
  • E. Potosí Department
    Potosí Department is a high-altitude region in southwestern Bolivia known for its historic silver mining city of Potosí and vast Andean landscapes.
  • 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_69a885ffc5ec819091afa325d5f9611c completed March 4, 2026, 7:20 p.m.
NER Named-entity recognition batch_69a909abbec081908f95547471530ad5 completed March 5, 2026, 4:42 a.m.
NED1 Entity disambiguation (via context triple) batch_69add1ac4b9c8190a7d0fa610a77f9c3 completed March 8, 2026, 7:44 p.m.
Created at: March 4, 2026, 7:28 p.m.