Triple
T111051
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Juan de Fuca Plate |
E2247
|
entity |
| Predicate | hazardRelevance |
P583
|
FINISHED |
| Object | Cascadia megathrust earthquake 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: Cascadia megathrust earthquake risk | Statement: [Juan de Fuca Plate, hazardRelevance, Cascadia megathrust earthquake risk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hazardRelevance Context triple: [Juan de Fuca Plate, hazardRelevance, Cascadia megathrust earthquake risk]
-
A.
hazardType
Indicates the specific kind or category of hazard associated with an entity or situation.
-
B.
riskLevel
Indicates the degree of potential harm, loss, or adverse outcome associated with a particular situation, action, or entity.
-
C.
threatenedBy
Indicates that one entity poses a danger or potential harm to another entity.
-
D.
susceptibleTo
chosen
Indicates that one entity is vulnerable or likely to be affected, harmed, or influenced by another entity or factor.
-
E.
affectedAgency
Indicates that one entity has an effect on, or causes a change in, the agency or capacity for action of another 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_69a24fcdaeb48190a2d796677e4b3281 |
completed | Feb. 28, 2026, 2:15 a.m. |
| NER | Named-entity recognition | batch_69a258b58efc8190959c86f73d67b744 |
completed | Feb. 28, 2026, 2:53 a.m. |
| PD | Predicate disambiguation | batch_69a25641058c8190b5b64509b35d8176 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:20 a.m.