Triple
T669153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | North Sea flood of 1953 |
E12932
|
entity |
| Predicate | areaInundatedNetherlands |
P18127
|
FINISHED |
| Object | over 150000 hectares |
—
|
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: over 150000 hectares | Statement: [North Sea flood of 1953, areaInundatedNetherlands, over 150000 hectares]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: areaInundatedNetherlands Context triple: [North Sea flood of 1953, areaInundatedNetherlands, over 150000 hectares]
-
A.
areaWater
Indicates the relationship between a geographic entity and the total area of its surface that is covered by water.
-
B.
hasFloodRisk
Indicates that an entity is exposed to a potential or expected risk of flooding under certain conditions.
-
C.
hasFloodplain
Indicates that an area or location lies within the floodplain associated with a particular water body or flooding source.
-
D.
drainageBasinArea
Indicates the total surface area of land from which precipitation and runoff drain into a particular water body or watershed.
-
E.
landArea
Indicates the total surface area of a piece of land associated with an entity, typically measured in standardized units (e.g., square meters, hectares).
- F. None of above. chosen
Provenance (4 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_69a493355dec819098d4244b2fa34885 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49ffbe09881909b547a52a6b34c7f |
completed | March 1, 2026, 8:22 p.m. |
| PD | Predicate disambiguation | batch_69a49d18942c819083b3d1887e505900 |
completed | March 1, 2026, 8:10 p.m. |
| PDg | Predicate description generation | batch_69a49fcf0cb4819096edea4037ca2c03 |
completed | March 1, 2026, 8:21 p.m. |
Created at: March 1, 2026, 7:36 p.m.