Triple
T32548453
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Economy of Burundi |
E831907
|
entity |
| Predicate | exportConcentration |
P60326
|
FINISHED |
| Object | high in coffee and tea |
—
|
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 in coffee and tea | Statement: [Economy of Burundi, exportConcentration, high in coffee and tea]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: exportConcentration Context triple: [Economy of Burundi, exportConcentration, high in coffee and tea]
-
A.
concentration
Indicates the degree to which a substance or entity is present within a given medium, mixture, or space.
-
B.
concentrationComponent
Indicates that one entity is a constituent or ingredient whose amount contributes to the overall concentration of another entity (such as a mixture, solution, or sample).
-
C.
commonConcentration
Indicates that multiple entities share the same concentration level of a specified substance or component.
-
D.
concentrationClass
chosen
Indicates the classification of an entity based on the level or range of its concentration.
-
E.
concentrates
Indicates that one entity directs its attention, effort, or resources intensely toward a specific target, task, or area.
- 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_69f6c8159edc8190b1c87015e0c820e8 |
completed | May 3, 2026, 3:59 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f42fbc8190a06eb1044c9e6094 |
completed | May 3, 2026, 3:41 a.m. |
Created at: May 1, 2026, 1:02 a.m.