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.