Triple
T23361099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Banyang-Mbo Wildlife Sanctuary |
E593184
|
entity |
| Predicate | nearbyHumanCommunities |
P4647
|
FINISHED |
| Object | Banyang people |
—
|
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: Banyang people | Statement: [Banyang-Mbo Wildlife Sanctuary, nearbyHumanCommunities, Banyang people]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyHumanCommunities Context triple: [Banyang-Mbo Wildlife Sanctuary, nearbyHumanCommunities, Banyang people]
-
A.
nearbySettlements
Indicates that one settlement is located close to another settlement in geographic space.
-
B.
hasNearbyCommunity
chosen
Indicates that one entity has another community located close to it in geographic or spatial terms.
-
C.
nearbySettlementRegion
Indicates that a settlement is located close to or within the surrounding area of a specified region.
-
D.
nearbyNativeGroups
Indicates that there are indigenous or native groups located in close geographic proximity to the referenced entity.
-
E.
nearbySettlementUS
Indicates that one settlement is geographically close to another settlement within the United States.
- 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_69e25d24d2a4819092e6ede74c2a918d |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f1a0a730f8819088fec53a43b063f8 |
completed | April 29, 2026, 6:09 a.m. |
| PD | Predicate disambiguation | batch_69f061c7aaa48190a58ce93f87155ffc |
completed | April 28, 2026, 7:29 a.m. |
Created at: April 17, 2026, 5:30 p.m.