Triple
T33778324
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mau Forest |
E865582
|
entity |
| Predicate | isOneOfLargestClosedCanopyForestsIn |
P180755
|
FINISHED |
| Object | East Africa |
—
|
NE NERFINISHED |
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: East Africa | Statement: [Mau Forest, isOneOfLargestClosedCanopyForestsIn, East Africa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isOneOfLargestClosedCanopyForestsIn Context triple: [Mau Forest, isOneOfLargestClosedCanopyForestsIn, East Africa]
-
A.
isLargestIndigenousForestIn
Indicates that a forest is the largest indigenous (native) forest within a specified geographic area or region.
-
B.
hasMajorRainforest
Indicates that one entity possesses or contains a large, significant rainforest within its area or domain.
-
C.
isOneOfLargestPlantsOf
Indicates that the subject is among the largest plants within the group or category specified by the object.
-
D.
notableForestAreas
Indicates that there exists a forested region associated with the subject that is recognized as significant or noteworthy in some context.
-
E.
forestArea
Indicates the extent or size of land covered by forest within a given area or region.
- 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_69f3498df6f88190bf9647ea4e4a956e |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f74c70fd248190a9d5543afcb08211 |
completed | May 3, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69f7478e3b548190a51d5d436e2bb036 |
completed | May 3, 2026, 1:03 p.m. |
| PDg | Predicate description generation | batch_69f74c6fa6548190b03935f65429a24e |
completed | May 3, 2026, 1:23 p.m. |
Created at: May 1, 2026, 1:45 a.m.