Triple
T36666728
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rwandan highlands |
E905284
|
entity |
| Predicate | majorCashCrops |
P200979
|
FINISHED |
| Object | coffee |
—
|
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: coffee | Statement: [Rwandan highlands, majorCashCrops, coffee]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorCashCrops Context triple: [Rwandan highlands, majorCashCrops, coffee]
-
A.
majorCrop
Indicates that a particular crop is one of the primary or most important crops cultivated in a given area or context.
-
B.
majorCropSpecies
chosen
Indicates that the object is a primary or dominant crop species cultivated in the subject region or context.
-
C.
cultivatedPrimarilyIn
Indicates that something is mainly grown, produced, or farmed in a particular place or environment.
-
D.
agriculturalProduce
Indicates that one entity is an agricultural product (such as crops or livestock-derived goods) produced by or associated with another entity.
-
E.
agricultureShareOfGDP
Indicates the proportion of a country’s total economic output (GDP) that is generated by agricultural activities.
- 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_69f76e6f10008190aea41746aa1b186e |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69ffc605b0648190a7abe9128b0d857a |
completed | May 9, 2026, 11:40 p.m. |
| PD | Predicate disambiguation | batch_69ffc5742d80819099f947ece78d5700 |
completed | May 9, 2026, 11:38 p.m. |
Created at: May 3, 2026, 4:12 p.m.