Triple
T710467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | River Medlock |
E14193
|
entity |
| Predicate | hasFloodRiskIssues |
P12640
|
FINISHED |
| Object | local urban 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: local urban flooding | Statement: [River Medlock, hasFloodRiskIssues, local urban flooding]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFloodRiskIssues Context triple: [River Medlock, hasFloodRiskIssues, local urban flooding]
-
A.
hasFloodRisk
chosen
Indicates that an entity is exposed to a potential or expected risk of flooding under certain conditions.
-
B.
hasFloodplain
Indicates that an area or location lies within the floodplain associated with a particular water body or flooding source.
-
C.
hasSeasonalFlooding
Indicates that an area regularly experiences flooding during specific, recurring times of the year.
-
D.
hasFloodHistory
Indicates that the subject has experienced one or more flood events in the past.
-
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_69a493494ec48190ae6751683625a9ba |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a77fcc6881908a025bb21e44ad56 |
completed | March 1, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69a4a4f221b081909fbaa689fb20eb3e |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:36 p.m.