Triple
T5948148
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Region (Cameroon) |
E132329
|
entity |
| Predicate | predominantLandscape |
P9701
|
FINISHED |
| Object | savanna |
—
|
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: savanna | Statement: [North Region (Cameroon), predominantLandscape, savanna]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: predominantLandscape Context triple: [North Region (Cameroon), predominantLandscape, savanna]
-
A.
landscapeType
chosen
Indicates the kind or category of natural terrain or scenery that characterizes a place or area.
-
B.
landerType
Indicates the specific kind or category of lander involved in the relationship or action.
-
C.
landscapeStyle
Indicates the design style or aesthetic approach applied to a landscape or outdoor environment.
-
D.
hasLandscapeFeatures
Indicates that an entity possesses or includes specific landscape-related characteristics or elements.
-
E.
naturalRegionType
Indicates the type or category of natural region to which a given area or place belongs.
- 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_69c00869d3308190af89b2453e0f7546 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c03ee10b308190afe38b904ae7c5f7 |
completed | March 22, 2026, 7:11 p.m. |
| PD | Predicate disambiguation | batch_69c0335806788190b6488ca8b73f7a63 |
completed | March 22, 2026, 6:22 p.m. |
Created at: March 22, 2026, 4:01 p.m.