Triple

T5764517
Position Surface form Disambiguated ID Type / Status
Subject Uyuni E127176 entity
Predicate hasRailConnectionTo P848 FINISHED
Object Oruro E39084 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: Oruro | Statement: [Uyuni, hasRailConnectionTo, Oruro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oruro
Context triple: [Uyuni, hasRailConnectionTo, Oruro]
  • A. Oruro chosen
    Oruro is a city in western Bolivia best known for its rich mining history and its UNESCO-recognized Carnival, one of South America's most famous folkloric festivals.
  • B. Caranavi
    Caranavi is a Bolivian town known as a key coffee-growing and agricultural hub in the Yungas region.
  • C. Saña
    Saña is a historic town in northern Peru known for its colonial heritage and association with early Spanish ecclesiastical figures.
  • D. Candelaria
    Candelaria is a municipality in western Cuba known for its agricultural activities and rural communities within Artemisa Province.
  • E. Candelaria
    Candelaria is a barrio (district) of the municipality of Toa Baja in Puerto Rico, functioning as one of its primary local administrative and residential communities.
  • 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_69c00833a3fc81908f4bc29ed011b7a6 completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c0296e12d48190bd120879723bb6e8 completed March 22, 2026, 5:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69c07e59c2d0819091101dea300e1d7e completed March 22, 2026, 11:42 p.m.
Created at: March 22, 2026, 3:49 p.m.