Triple

T6830856
Position Surface form Disambiguated ID Type / Status
Subject Northwestern Mexico E157131 entity
Predicate hasTouristDestination P6629 FINISHED
Object La Paz E166268 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 | Statement: [Northwestern Mexico, hasTouristDestination, La Paz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: La Paz
Context triple: [Northwestern Mexico, hasTouristDestination, La Paz]
  • A. La Paz
    La Paz is the administrative capital and one of the major cities of Bolivia, known for its dramatic setting in a deep valley of the Andes at one of the highest elevations of any capital city in the world.
  • B. La Paz chosen
    La Paz is the capital city of Baja California Sur in Mexico, known for its coastal location on the Gulf of California, marine biodiversity, and laid-back seaside atmosphere.
  • C. La Paz
    La Paz is a municipality in the province of Tarlac in the Philippines, known for its agricultural economy and role as a local commercial center.
  • D. La Paz
    La Paz is a municipality in the State of Mexico that forms part of the greater Mexico City metropolitan area.
  • E. La Paz
    La Paz is a city in northeastern Argentina known for its location on the Paraná River and its role as a regional center in Entre Ríos Province.
  • 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_69c6882a5b5c8190917a7db9ed36bad1 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6d62820808190ad3c244893e88699 completed March 27, 2026, 7:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69c748b244008190b0b373a67799ffa1 completed March 28, 2026, 3:19 a.m.
Created at: March 27, 2026, 2:18 p.m.