Triple
T34915353
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | South Africa–Botswana border |
E1006984
|
entity |
| Predicate | generalEnvironment |
P111300
|
FINISHED |
| Object | sparsely populated |
—
|
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: sparsely populated | Statement: [South Africa–Botswana border, generalEnvironment, sparsely populated]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: generalEnvironment Context triple: [South Africa–Botswana border, generalEnvironment, sparsely populated]
-
A.
environmentType
Indicates the kind or category of environment associated with an entity or situation.
-
B.
general
Indicates that one entity has a broad, non-specific, or overarching relationship or association with another entity.
-
C.
hasGeneralEnvironment
chosen
Indicates that an entity exists or operates within a broad or overall environmental context or setting.
-
D.
generalCategory
Indicates that one entity is classified as a broad or overarching category to which the other entity belongs.
-
E.
environmentalMedium
Indicates the environmental context or medium (such as air, water, or soil) through which a substance, effect, or process occurs or is present.
- 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_69f76dc2b6b0819095a61debbd405269 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f78c61ed4c8190ad84c918fa9af55a |
completed | May 3, 2026, 5:56 p.m. |
| PD | Predicate disambiguation | batch_69f78b8cb3a881909ebaac1b503988c2 |
completed | May 3, 2026, 5:53 p.m. |
Created at: May 3, 2026, 4 p.m.