Triple
T5275370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Indonesia Center for Volcanology and Geological Hazard Mitigation |
E119359
|
entity |
| Predicate | typeOfHazard |
P1950
|
FINISHED |
| Object | volcanic eruptions |
—
|
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: volcanic eruptions | Statement: [Indonesia Center for Volcanology and Geological Hazard Mitigation, typeOfHazard, volcanic eruptions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typeOfHazard Context triple: [Indonesia Center for Volcanology and Geological Hazard Mitigation, typeOfHazard, volcanic eruptions]
-
A.
hazardType
chosen
Indicates the specific kind or category of hazard associated with an entity or situation.
-
B.
hasNotableHazard
Indicates that an entity is associated with a significant risk, danger, or harmful condition that is noteworthy or exceptional.
-
C.
hazardScope
Indicates the range or extent within which a particular hazard is relevant, applicable, or has effect.
-
D.
hasHazardLevel
Indicates that an entity is associated with a specified degree or category of risk or danger.
-
E.
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).
- 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_69bd446c38e081908cdaf113bdf86790 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd8c9c72b08190947b6b955ac1bb5a |
completed | March 20, 2026, 6:06 p.m. |
| PD | Predicate disambiguation | batch_69bd844a56b48190ad743c42246e02dd |
completed | March 20, 2026, 5:30 p.m. |
Created at: March 20, 2026, 1:51 p.m.