Triple

T19396828
Position Surface form Disambiguated ID Type / Status
Subject Oxapampa Province E485211 entity
Predicate hasBiome P952 FINISHED
Object Amazonian cloud forest NE NERFINISHED

How this triple was built (3 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: Amazonian cloud forest | Statement: [Oxapampa Province, hasBiome, Amazonian cloud forest]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Amazonian cloud forest
Context triple: [Oxapampa Province, hasBiome, Amazonian cloud forest]
  • A. Chocó–Darién moist forests
    The Chocó–Darién moist forests are a highly biodiverse tropical rainforest ecoregion along the Pacific coast of Colombia and Panama, known for extreme rainfall, rich endemic species, and largely intact wilderness.
  • B. Gamboa Rainforest
    Gamboa Rainforest is a lush tropical rainforest area near the Panama Canal known for its rich biodiversity, ecotourism lodges, and wildlife observation opportunities.
  • C. Southwest Amazon moist forests
    The Southwest Amazon moist forests are a highly biodiverse tropical rainforest ecoregion spanning parts of Peru, Brazil, and Bolivia, known for its rich wildlife, extensive river systems, and relatively intact primary forest.
  • D. Napo moist forests
    Napo moist forests are a biodiverse tropical rainforest ecoregion in the western Amazon Basin, spanning parts of Peru, Ecuador, and Colombia and renowned for their exceptionally high species richness and endemism.
  • E. Andean forests
    Andean forests are high-altitude, biodiverse mountain woodlands along the Andes, characterized by cool, moist climates and rich assemblages of endemic plants and animals.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Amazonian cloud forest
Target entity description: The Amazonian cloud forest is a high-elevation, tropical rainforest ecosystem characterized by persistent mist, exceptional biodiversity, and dense, moisture-loving vegetation along the eastern slopes of the Andes.
  • A. Chocó–Darién moist forests
    The Chocó–Darién moist forests are a highly biodiverse tropical rainforest ecoregion along the Pacific coast of Colombia and Panama, known for extreme rainfall, rich endemic species, and largely intact wilderness.
  • B. Gamboa Rainforest
    Gamboa Rainforest is a lush tropical rainforest area near the Panama Canal known for its rich biodiversity, ecotourism lodges, and wildlife observation opportunities.
  • C. Southwest Amazon moist forests
    The Southwest Amazon moist forests are a highly biodiverse tropical rainforest ecoregion spanning parts of Peru, Brazil, and Bolivia, known for its rich wildlife, extensive river systems, and relatively intact primary forest.
  • D. Napo moist forests
    Napo moist forests are a biodiverse tropical rainforest ecoregion in the western Amazon Basin, spanning parts of Peru, Ecuador, and Colombia and renowned for their exceptionally high species richness and endemism.
  • E. Andean forests chosen
    Andean forests are high-altitude, biodiverse mountain woodlands along the Andes, characterized by cool, moist climates and rich assemblages of endemic plants and animals.
  • F. None of above.

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_69d8e8d5162481909db12435d9535c1a completed April 10, 2026, 12:11 p.m.
NER Named-entity recognition batch_69e62573f5788190a635b92121db2cf7 completed April 20, 2026, 1:09 p.m.
Created at: April 10, 2026, 1:36 p.m.