Triple
T3198802
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mwinilunga District |
E66994
|
entity |
| Predicate | hasHighRainfall |
P17982
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Mwinilunga District, hasHighRainfall, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHighRainfall Context triple: [Mwinilunga District, hasHighRainfall, true]
-
A.
hasFloodRisk
Indicates that an entity is exposed to a potential or expected risk of flooding under certain conditions.
-
B.
hasSeasonalFlooding
Indicates that an area regularly experiences flooding during specific, recurring times of the year.
-
C.
hasExtremeWeatherCharacteristic
chosen
Indicates that something possesses a notable or defining feature related to extreme weather conditions.
-
D.
rainfallPeak
Indicates the time or value at which rainfall intensity reaches its maximum during a given period or event.
-
E.
hasSevereWeatherRisk
Indicates that an entity is exposed to or associated with a high likelihood of severe or hazardous weather conditions.
- 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_69ad8589bd988190afa7ed2bdffb7b33 |
completed | March 8, 2026, 2:19 p.m. |
| NER | Named-entity recognition | batch_69ada9abe8f88190a4c2ccc31add7959 |
completed | March 8, 2026, 4:54 p.m. |
| PD | Predicate disambiguation | batch_69ad9e05e4f48190adbe4366cdba2349 |
completed | March 8, 2026, 4:04 p.m. |
Created at: March 8, 2026, 3:07 p.m.