Triple
T5856943
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tropical rain forest |
E130177
|
entity |
| Predicate | hasVegetationLayer |
P67517
|
FINISHED |
| Object | emergent layer |
—
|
LITERAL 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: emergent layer | Statement: [Tropical rain forest, hasVegetationLayer, emergent layer]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVegetationLayer Context triple: [Tropical rain forest, hasVegetationLayer, emergent layer]
-
A.
hasVegetationIssue
Indicates that an entity is affected by a problem, damage, or abnormal condition related to its vegetation or plant life.
-
B.
vegetationType
Indicates the specific kind or category of plant cover or flora that characterizes a given area or environment.
-
C.
vegetation
Indicates that an area or object is covered with, contains, or is characterized by plant life.
-
D.
hasAttractiveFoliage
Indicates that an entity possesses foliage that is visually appealing or ornamental in appearance.
-
E.
hasCanopyDensity
Indicates the degree to which a canopy (such as a tree or forest cover) occupies or obscures the area beneath it.
- F. None of above. chosen
Provenance (4 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_69c0084f3bb08190a7720f55f7aa4252 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c044ab0a048190b84be40fb13c0f50 |
completed | March 22, 2026, 7:36 p.m. |
| PD | Predicate disambiguation | batch_69c03345ca0c819081c81148d054fed2 |
completed | March 22, 2026, 6:21 p.m. |
| PDg | Predicate description generation | batch_69c044a9c4f0819081b8c196932883f6 |
completed | March 22, 2026, 7:36 p.m. |
Created at: March 22, 2026, 3:56 p.m.