Triple
T13272617
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Palu Bay |
E316101
|
entity |
| Predicate | naturalHazardZone |
P38433
|
FINISHED |
| Object | tsunami-prone 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: tsunami-prone area | Statement: [Palu Bay, naturalHazardZone, tsunami-prone area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: naturalHazardZone Context triple: [Palu Bay, naturalHazardZone, tsunami-prone area]
-
A.
geologicalHazardZoneFor
chosen
Indicates a relationship where a specified area or zone is identified as being at risk from a particular geological hazard (such as earthquakes, landslides, or volcanic activity).
-
B.
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).
-
C.
relatedEarthquakeZone
Indicates that one entity is geographically or geologically associated with a particular earthquake-prone zone or seismic region.
-
D.
frequentNaturalHazard
Indicates that a location or area regularly experiences natural hazards such as floods, earthquakes, storms, or similar events with notable frequency.
-
E.
earthquakeHazardLevel
Indicates the assessed degree of risk or potential impact from earthquakes associated with a given location or 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_69d806b1d9ac8190852c5571d5bd5f0f |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d99cfdc9388190af1fdd3cd4717bd8 |
completed | April 11, 2026, 12:59 a.m. |
| PD | Predicate disambiguation | batch_69d98f6535688190a5a4549b7be2d611 |
completed | April 11, 2026, 12:01 a.m. |
Created at: April 9, 2026, 9:26 p.m.