Triple
T34196604
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lealui |
E877258
|
entity |
| Predicate | floodPattern |
P158858
|
FINISHED |
| Object | area subject to annual Zambezi flooding |
—
|
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: area subject to annual Zambezi flooding | Statement: [Lealui, floodPattern, area subject to annual Zambezi flooding]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: floodPattern Context triple: [Lealui, floodPattern, area subject to annual Zambezi flooding]
-
A.
floodType
Indicates the specific kind or category of flooding involved in an event or situation.
-
B.
floodEnhancedBy
Indicates that the occurrence, intensity, or impact of a flood is increased or made more severe by the associated factor or condition.
-
C.
floodFrequency
chosen
Indicates how often flooding occurs or is expected to occur at a given location or under specified conditions.
-
D.
floodEvent
Indicates an occurrence of a flooding event affecting a location, time period, or set of impacted entities.
-
E.
drainagePattern
Indicates the characteristic spatial arrangement and connectivity of natural or artificial drainage features (such as streams, channels, or pipes) within an area.
- 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_69f349af20a4819089ac24d28f2d8112 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f710296d748190badcd84374991840 |
completed | May 3, 2026, 9:06 a.m. |
| PD | Predicate disambiguation | batch_69f70f3c5bfc81908585f52e196dafe5 |
completed | May 3, 2026, 9:02 a.m. |
Created at: May 1, 2026, 1:55 a.m.