Triple
T16751688
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Southern Cameroon |
E407096
|
entity |
| Predicate | hasGeographicPosition |
P80554
|
FINISHED |
| Object | southern part of Cameroon |
—
|
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: southern part of Cameroon | Statement: [Southern Cameroon, hasGeographicPosition, southern part of Cameroon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasGeographicPosition Context triple: [Southern Cameroon, hasGeographicPosition, southern part of Cameroon]
-
A.
hasGeocode
Indicates that an entity is associated with a specific geographic coordinate or coded location reference.
-
B.
hasGeographicType
Indicates that an entity is associated with or classified by a specific type or category of geographic feature or area.
-
C.
hasGeographicBasis
Indicates that something is grounded in, derived from, or defined by a particular geographic location or area.
-
D.
hasCoordinates
Indicates that an entity is associated with specific spatial coordinates that define its position in a given reference system.
-
E.
hasRegionalPosition
chosen
Indicates that one entity holds a specific role, status, or placement within a defined geographic or regional context relative to another entity.
- 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_69d8838ffb088190a0b11149929006bf |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3aa271de48190b4a535408aeef734 |
completed | April 18, 2026, 3:58 p.m. |
| PD | Predicate disambiguation | batch_69e319cbd79c8190a03587a61c18bec0 |
completed | April 18, 2026, 5:42 a.m. |
Created at: April 10, 2026, 5:21 a.m.