Triple
T29585479
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | belg rainy season (Ethiopia) |
E753707
|
entity |
| Predicate | mainBeneficiaryRegions |
P3060
|
FINISHED |
| Object | central Ethiopia |
—
|
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: central Ethiopia | Statement: [belg rainy season (Ethiopia), mainBeneficiaryRegions, central Ethiopia]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainBeneficiaryRegions Context triple: [belg rainy season (Ethiopia), mainBeneficiaryRegions, central Ethiopia]
-
A.
beneficiaryRegion
chosen
Indicates the region that receives the benefit, advantage, or positive impact resulting from an action, resource, or arrangement.
-
B.
benefitedCountry
Indicates that one country gains an advantage, profit, or positive outcome from an action, event, or entity associated with another.
-
C.
beneficiaryStates
Indicates that certain states receive benefits, advantages, or positive outcomes from a particular action, event, or arrangement.
-
D.
beneficiaryCountry
Indicates that one country is the recipient or beneficiary of aid, resources, or advantages provided in a given context.
-
E.
issuerRegionServed
Indicates the geographic region or area that the issuer provides services to or operates within.
- 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, 6:10 p.m.