Triple
T16301712
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zimbabwe and Mozambique |
E395804
|
entity |
| Predicate | shareDisasterRisk |
P77303
|
FINISHED |
| Object | flooding in shared river basins |
—
|
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: flooding in shared river basins | Statement: [Zimbabwe and Mozambique, shareDisasterRisk, flooding in shared river basins]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shareDisasterRisk Context triple: [Zimbabwe and Mozambique, shareDisasterRisk, flooding in shared river basins]
-
A.
shareFloodRisk
chosen
Indicates that two or more entities are exposed to the same or overlapping risk of flooding.
-
B.
disasterLocation
Indicates the place where a disaster occurs or has its primary impact.
-
C.
riskToEarth
Indicates that something poses a potential threat, danger, or harmful impact to Earth.
-
D.
causeOfDisaster
Indicates that the subject is responsible for bringing about or triggering the specified disaster.
-
E.
hasNaturalHazardRisk
Indicates that an entity is exposed or subject to potential damage or impact from one or more natural hazards (e.g., earthquakes, floods, storms).
- 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_69d87f23bb088190a16fbb91a1957ea5 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e25e32da7081908d8bd320374a5731 |
completed | April 17, 2026, 4:22 p.m. |
| PD | Predicate disambiguation | batch_69e219fa5508819097e9d383348bf174 |
completed | April 17, 2026, 11:31 a.m. |
Created at: April 10, 2026, 5:06 a.m.