Triple
T5404131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Peruvian Amazon |
E120848
|
entity |
| Predicate | ecoregion |
P948
|
FINISHED |
| Object |
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.
|
E520941
|
NE FINISHED |
How this triple was built (4 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: Napo moist forests | Statement: [Peruvian Amazon, ecoregion, Napo moist forests]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Napo moist forests Context triple: [Peruvian Amazon, ecoregion, Napo moist forests]
-
A.
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.
-
B.
Guayanan moist forests
Guayanan moist forests are a vast tropical rainforest ecoregion of the Guiana Shield in northern South America, noted for their high biodiversity, dense evergreen canopy, and largely intact, remote wilderness.
-
C.
Tapajós–Xingu moist forests
The Tapajós–Xingu moist forests are a biodiverse tropical rainforest ecoregion in the central Brazilian Amazon, known for its rich endemic wildlife and extensive, relatively undisturbed forest cover between the Tapajós and Xingu rivers.
-
D.
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.
-
E.
Tropical Rain Forest
Tropical Rain Forest is a lush, biodiverse ecosystem characterized by high rainfall, dense vegetation, and an extraordinary variety of plant and animal life.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Napo moist forests Triple: [Peruvian Amazon, ecoregion, Napo moist forests]
Generated description
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.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Napo moist forests Target entity description: 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.
-
A.
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.
-
B.
Guayanan moist forests
Guayanan moist forests are a vast tropical rainforest ecoregion of the Guiana Shield in northern South America, noted for their high biodiversity, dense evergreen canopy, and largely intact, remote wilderness.
-
C.
Tapajós–Xingu moist forests
The Tapajós–Xingu moist forests are a biodiverse tropical rainforest ecoregion in the central Brazilian Amazon, known for its rich endemic wildlife and extensive, relatively undisturbed forest cover between the Tapajós and Xingu rivers.
-
D.
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.
-
E.
Tropical Rain Forest
Tropical Rain Forest is a lush, biodiverse ecosystem characterized by high rainfall, dense vegetation, and an extraordinary variety of plant and animal life.
- F. None of above. chosen
Provenance (5 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_69bd46391c0c81909fa484446732b6a3 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd8774cd8881909b3437ba02018444 |
completed | March 20, 2026, 5:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf411f8f3c81908ca8578a388261c6 |
completed | March 22, 2026, 1:08 a.m. |
| NEDg | Description generation | batch_69bf42ef2484819088905be590e0399a |
completed | March 22, 2026, 1:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf43732118819099eee5dcae3715dc |
completed | March 22, 2026, 1:18 a.m. |
Created at: March 20, 2026, 2:04 p.m.