Triple
T12963533
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Af (Köppen) |
E321206
|
entity |
| Predicate | associatedVegetation |
P83264
|
FINISHED |
| Object | evergreen broadleaf forest |
—
|
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: evergreen broadleaf forest | Statement: [Af (Köppen), associatedVegetation, evergreen broadleaf forest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedVegetation Context triple: [Af (Köppen), associatedVegetation, evergreen broadleaf forest]
-
A.
associatedFlora
chosen
Indicates a relationship where specific plants or vegetation are characteristically linked to, occur with, or are commonly found in association with a given entity or environment.
-
B.
vegetation
Indicates that an area or object is covered with, contains, or is characterized by plant life.
-
C.
vegetationType
Indicates the specific kind or category of plant cover or flora that characterizes a given area or environment.
-
D.
involvesPlant
Indicates that the relationship or action includes or pertains to a plant as a participating entity.
-
E.
hasAttractiveFoliage
Indicates that an entity possesses foliage that is visually appealing or ornamental in appearance.
- F. None of above.
Provenance (3 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_69d80763bd6c819094437da5b20b01d2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d97e59a4c88190907d05b8d57dae89 |
completed | April 10, 2026, 10:48 p.m. |
| PD | Predicate disambiguation | batch_69d97dba57988190b786ffed55687a72 |
completed | April 10, 2026, 10:46 p.m. |
Created at: April 9, 2026, 8:25 p.m.