Triple
T25518803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kuiseb River |
E639583
|
entity |
| Predicate | averageAnnualRainfallInCatchment |
P472
|
FINISHED |
| Object | low and highly variable |
—
|
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: low and highly variable | Statement: [Kuiseb River, averageAnnualRainfallInCatchment, low and highly variable]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: averageAnnualRainfallInCatchment Context triple: [Kuiseb River, averageAnnualRainfallInCatchment, low and highly variable]
-
A.
averageAnnualPrecipitation
chosen
Indicates the typical total amount of precipitation an entity receives over the course of a year, averaged across multiple years.
-
B.
collectsRainfallFor
Indicates that one entity gathers or measures rainfall on behalf of, or for the benefit of, another entity.
-
C.
reservoirCatchment
Indicates that one entity is the catchment area that drains water into a specified reservoir.
-
D.
rainfallLevel
Indicates the amount or intensity of rainfall occurring at a given place and time.
-
E.
watershedArea
Indicates the total land area from which surface water drains into a particular water body or point in the drainage system.
- 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_69e75dbe32e48190a62d749a0ff2a96a |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f5f8346c1481908272a96740bf51bc |
completed | May 2, 2026, 1:12 p.m. |
| PD | Predicate disambiguation | batch_69f49377411c8190b2188de444d76795 |
completed | May 1, 2026, 11:50 a.m. |
Created at: April 21, 2026, 2:58 p.m.