Triple
T29584801
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jimma |
E753691
|
entity |
| Predicate | coffeeTypeAssociated |
P72095
|
FINISHED |
| Object | Jimma coffee |
—
|
NE NERFINISHED |
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: Jimma coffee | Statement: [Jimma, coffeeTypeAssociated, Jimma coffee]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coffeeTypeAssociated Context triple: [Jimma, coffeeTypeAssociated, Jimma coffee]
-
A.
coffeeVariety
chosen
Indicates a relationship where a specific type or variety of coffee is associated with a coffee-related entity (such as a product, beverage, or plant).
-
B.
coffeeDesignationType
Indicates the specific classification or type designation assigned to a coffee (e.g., by quality, origin, or regulatory category).
-
C.
coffeeOrganization
Indicates a relationship where an organization is involved with coffee, such as producing, distributing, selling, or promoting it.
-
D.
coffeeDesignation
Indicates that one entity is designated or classified as a particular type, role, or category of coffee in relation to another entity.
-
E.
teaType
Indicates the specific variety or category of tea associated with an 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_69f0ef80bf8c8190ad286e99f7df0c63 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_69f66d7d3ac48190adef6aa96f5a5b45 |
completed | May 2, 2026, 9:32 p.m. |
| PD | Predicate disambiguation | batch_69f6659d36208190b01412600a4ed57d |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 28, 2026, 6:09 p.m.