Triple
T24741213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tzaneen |
E618562
|
entity |
| Predicate | locatedInVegetationZone |
P953
|
FINISHED |
| Object | subtropical fruit belt |
—
|
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: subtropical fruit belt | Statement: [Tzaneen, locatedInVegetationZone, subtropical fruit belt]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInVegetationZone Context triple: [Tzaneen, locatedInVegetationZone, subtropical fruit belt]
-
A.
locatedInForest
Indicates that an entity is situated within the boundaries of a forest.
-
B.
vegetationType
chosen
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.
hasVegetationRole
Indicates that an entity participates in or is assigned a specific functional role related to vegetation (such as growth, maintenance, or impact on plant life).
-
E.
isForested
Indicates that an area or region is covered predominantly by forest or dense tree vegetation.
- 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_69e2fab8f95c81908bb9e552cf3280c2 |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f497bc12b881908fe3386c66252bf6 |
completed | May 1, 2026, 12:08 p.m. |
| PD | Predicate disambiguation | batch_69f49366e8d08190adb4b71fe3a14683 |
completed | May 1, 2026, 11:49 a.m. |
Created at: April 18, 2026, 4:12 a.m.