Triple
T543034
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Limpopo River |
E12671
|
entity |
| Predicate | hasFloodEvents |
P13044
|
FINISHED |
| Object | subject to seasonal 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: subject to seasonal flooding | Statement: [Limpopo River, hasFloodEvents, subject to seasonal flooding]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFloodEvents Context triple: [Limpopo River, hasFloodEvents, subject to seasonal flooding]
-
A.
hasFloodRisk
Indicates that an entity is exposed to a potential or expected risk of flooding under certain conditions.
-
B.
hasSeasonalFlooding
chosen
Indicates that an area regularly experiences flooding during specific, recurring times of the year.
-
C.
hasFloodplain
Indicates that an area or location lies within the floodplain associated with a particular water body or flooding source.
-
D.
hasRiverActivity
Indicates that an entity engages in, supports, or is associated with activities occurring on or along a river.
-
E.
hasFloodProtectionProject
Indicates that a flood protection project exists or is implemented for the referenced entity.
- 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_69a49334226c81908b0ea1689ef6aa3f |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4986250508190ac91cfdf7d57073d |
completed | March 1, 2026, 7:49 p.m. |
| PD | Predicate disambiguation | batch_69a494b8098481908097228db8ad0262 |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:32 p.m.