Triple
T612177
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mount Kilimanjaro |
E12121
|
entity |
| Predicate | hasVegetationZone |
P949
|
FINISHED |
| Object | cultivated lower slopes |
—
|
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: cultivated lower slopes | Statement: [Mount Kilimanjaro, hasVegetationZone, cultivated lower slopes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVegetationZone Context triple: [Mount Kilimanjaro, hasVegetationZone, cultivated lower slopes]
-
A.
vegetationType
Indicates the specific kind or category of plant cover or flora that characterizes a given area or environment.
-
B.
vegetation
chosen
Indicates that an area or object is covered with, contains, or is characterized by plant life.
-
C.
hasZone
Indicates that one entity possesses, contains, or is associated with a specific zone or designated area.
-
D.
hasTrees
Indicates that something possesses or contains one or more trees.
-
E.
hasCanopy
Indicates that one entity possesses or is characterized by a canopy associated with it.
- 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_69a493309df48190a327f748e88049a6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49e07739481909930a6577c081b9e |
completed | March 1, 2026, 8:13 p.m. |
| PD | Predicate disambiguation | batch_69a49cfa7b4481909bec7a5fd3e98c65 |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:35 p.m.