Triple
T32548452
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Economy of Burundi |
E831907
|
entity |
| Predicate | laborForceShareInAgriculture |
P72303
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Economy of Burundi, laborForceShareInAgriculture, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laborForceShareInAgriculture Context triple: [Economy of Burundi, laborForceShareInAgriculture, high]
-
A.
hasAgriculturalLaborForce
chosen
Indicates that an entity possesses a workforce engaged in agricultural activities or farming-related labor.
-
B.
agriculturalDependence
Indicates that one entity relies on another for agricultural resources, production, or support.
-
C.
hasRuralAreaShare
Indicates the proportion of an entity’s total area or population that is classified as rural.
-
D.
hasRuralEconomySector
Indicates that an entity participates in, contains, or is associated with an economic sector based on rural activities or rural development.
-
E.
representsAgriculture
Indicates that one entity serves as an example, instance, or embodiment of agriculture in relation 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_69f34925fd08819084cfe4ec566cb704 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c5c3636c81908cb7b9418c47dbf0 |
completed | May 3, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2a14b081908162923dfbf0a6f4 |
completed | May 3, 2026, 3:12 a.m. |
Created at: May 1, 2026, 1:02 a.m.