Triple

T3408920
Position Surface form Disambiguated ID Type / Status
Subject Upper Peru E71842 entity
Predicate mainCity P3207 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: [Upper Peru, mainCity, Oruro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oruro
Context triple: [Upper Peru, mainCity, 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. Candelaria
    Candelaria is a municipality in western Cuba known for its agricultural activities and rural communities within Artemisa Province.
  • D. 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.
  • E. Candelaria
    Candelaria is a coastal town and important pilgrimage center on the island of Tenerife in Spain’s Canary Islands, known for the Basilica of Our Lady of Candelaria.
  • 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_69ad85ac312481909e7027ced1456a9f completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb9056acc8190a9c50ec374851ac8 completed March 8, 2026, 5:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69b34bdd99248190823875cae2531609 completed March 12, 2026, 11:27 p.m.
Created at: March 8, 2026, 3:15 p.m.