Triple
T24054821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Watari Town |
E595767
|
entity |
| Predicate | naturalHazardRisk |
P44599
|
FINISHED |
| Object | tsunami risk |
—
|
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: tsunami risk | Statement: [Watari Town, naturalHazardRisk, tsunami risk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: naturalHazardRisk Context triple: [Watari Town, naturalHazardRisk, tsunami risk]
-
A.
naturalHazardFunction
Indicates a functional relationship where an entity serves as, causes, or performs the role of a natural hazard (e.g., earthquake, flood, storm) affecting other entities or environments.
-
B.
hasNaturalHazardRisk
chosen
Indicates that an entity is exposed or subject to potential damage or impact from one or more natural hazards (e.g., earthquakes, floods, storms).
-
C.
frequentNaturalHazard
Indicates that a location or area regularly experiences natural hazards such as floods, earthquakes, storms, or similar events with notable frequency.
-
D.
riskToEarth
Indicates that something poses a potential threat, danger, or harmful impact to Earth.
-
E.
geologicHazardLevel
Indicates the degree of potential danger or risk posed by geologic processes or conditions at a given location.
- 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_69e288c184b081909f1f1751fb8e299a |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d9d551288190a2b3b6c8c4f3c1b5 |
completed | April 29, 2026, 10:13 a.m. |
| PD | Predicate disambiguation | batch_69f1764b1d4c8190b12590c6339c31c1 |
completed | April 29, 2026, 3:08 a.m. |
Created at: April 17, 2026, 10:22 p.m.