Triple

T8835085
Position Surface form Disambiguated ID Type / Status
Subject San Felipe de Austria Church E210246 entity
Predicate locatedIn P40 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: [San Felipe de Austria Church, locatedIn, Oruro]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Oruro
Context triple: [San Felipe de Austria Church, locatedIn, 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. Chepica
    Chepica is a small town and commune in central Chile’s O’Higgins Region, known for its agricultural activity and role within the Colchagua Valley wine area.
  • E. Candelaria
    Candelaria is a municipality in western Cuba known for its agricultural activities and rural communities within Artemisa 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_69ca8388549c819095fd94eadefbb007 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc60686cac8190b3138db40b6fe058 completed April 1, 2026, 12:01 a.m.
NED1 Entity disambiguation (via context triple) batch_69d0b165fb0c81908c79b6ade3cca20e completed April 4, 2026, 6:36 a.m.
Created at: March 30, 2026, 6:47 p.m.