Triple

T16107512
Position Surface form Disambiguated ID Type / Status
Subject Orellana Canton E390777 entity
Predicate locatedIn P40 FINISHED
Object Orellana Province NE NERFINISHED

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: Orellana Province | Statement: [Orellana Canton, locatedIn, Orellana Province]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Orellana Province
Context triple: [Orellana Canton, locatedIn, Orellana Province]
  • A. Orellana Province chosen
    Orellana Province is an Amazonian region in northeastern Ecuador known for its vast tropical rainforests, rich biodiversity, and significant oil reserves.
  • B. Caranavi Province
    Caranavi Province is an administrative province in Bolivia known for its coffee production and location within the Yungas region of the La Paz Department.
  • C. Eduardo Avaroa Province
    Eduardo Avaroa Province is an administrative division in the Oruro Department of Bolivia, known for its high-altitude Andean landscapes and rural mining communities.
  • D. Gualivá Province
    Gualivá Province is an administrative subdivision of the Cundinamarca Department in central Colombia, known for its mountainous terrain and agricultural towns.
  • E. Sud Yungas Province
    Sud Yungas Province is an administrative province in western Bolivia known for its mountainous terrain, cloud forests, and traditional coca-growing regions.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d87f1a8dd881909f1de6ef78849874 completed April 10, 2026, 4:39 a.m.
NER Named-entity recognition batch_69e1ff6e55c08190b77f344e4e8c42ad completed April 17, 2026, 9:37 a.m.
Created at: April 10, 2026, 5 a.m.