Triple
T70128
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Africa |
E1402
|
entity |
| Predicate | hasMajorEnvironmentalIssue |
P1006
|
FINISHED |
| Object | desertification |
—
|
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: desertification | Statement: [Africa, hasMajorEnvironmentalIssue, desertification]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMajorEnvironmentalIssue Context triple: [Africa, hasMajorEnvironmentalIssue, desertification]
-
A.
environmentalIssue
chosen
Indicates that something is a problem or concern related to the natural environment, such as harm, risk, or negative impact on ecosystems or resources.
-
B.
conservationIssue
Indicates that an entity is associated with a problem, threat, or concern related to the protection, preservation, or sustainable management of natural resources or biodiversity.
-
C.
hasMajorCurrent
Indicates that an entity currently has a primary field of study or specialization.
-
D.
hasMajorCommunity
Indicates that an entity possesses a primary or significantly large community associated with it.
-
E.
containsMajorClimatePhenomenon
Indicates that the subject region or area includes or experiences a significant, large-scale climate-related event or pattern.
- 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_69a24c06b3bc8190aa4ac89026115efc |
completed | Feb. 28, 2026, 1:59 a.m. |
| NER | Named-entity recognition | batch_69a24fd16c248190a6ee4cd96c388772 |
completed | Feb. 28, 2026, 2:15 a.m. |
| PD | Predicate disambiguation | batch_69a24eaa0df88190add55579b2b9fd02 |
completed | Feb. 28, 2026, 2:10 a.m. |
Created at: Feb. 28, 2026, 2:03 a.m.