Triple
T13336243
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | River Len |
E317699
|
entity |
| Predicate | hasFloodRiskRelevance |
P109076
|
FINISHED |
| Object | local flood management in Maidstone area |
—
|
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: local flood management in Maidstone area | Statement: [River Len, hasFloodRiskRelevance, local flood management in Maidstone area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFloodRiskRelevance Context triple: [River Len, hasFloodRiskRelevance, local flood management in Maidstone area]
-
A.
hasFloodRisk
Indicates that an entity is exposed to a potential or expected risk of flooding under certain conditions.
-
B.
floodRiskCategory
Indicates the level or classification of flood risk associated with an entity, such as a location or asset.
-
C.
hasFloodplain
Indicates that an area or location lies within the floodplain associated with a particular water body or flooding source.
-
D.
hasFloodplains
Indicates that an area or region includes land that is subject to flooding, typically adjacent to a river or water body.
-
E.
hasSeasonalFlooding
Indicates that an area regularly experiences flooding during specific, recurring times of the year.
- 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_69d806b5a3c08190b42c267fb092f98a |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99d00b75c8190af98784c7df904c8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f6e53d88190bd6aa42f69b10ffb |
completed | April 11, 2026, 12:01 a.m. |
| PDg | Predicate description generation | batch_69d99073e4708190843bda3a1ae78f43 |
completed | April 11, 2026, 12:06 a.m. |
Created at: April 9, 2026, 9:31 p.m.