Triple
T15633641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kyushu coastal areas |
E375881
|
entity |
| Predicate | vulnerabilitySource |
P119540
|
FINISHED |
| Object | Nankai Trough megathrust earthquakes |
—
|
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: Nankai Trough megathrust earthquakes | Statement: [Kyushu coastal areas, vulnerabilitySource, Nankai Trough megathrust earthquakes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vulnerabilitySource Context triple: [Kyushu coastal areas, vulnerabilitySource, Nankai Trough megathrust earthquakes]
-
A.
vulnerabilityType
Indicates the specific kind or category of vulnerability associated with an entity or situation.
-
B.
associatedWithVulnerability
Indicates a relationship where an entity is linked to, affected by, or relevant to a specific vulnerability or security weakness.
-
C.
threatIntelligenceSource
Indicates that one entity serves as the origin or provider of threat intelligence information for another entity.
-
D.
strategicVulnerability
Indicates a relationship where an entity is exposed to potential harm or disadvantage in a way that can be deliberately exploited within a strategic or competitive context.
-
E.
requiresSourceDisclosure
Indicates that performing or using something is contingent on revealing or making known the origin or source from which it was derived.
- F. None of above. chosen
Provenance (4 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_69d85cd035a48190b73d5579ab73969a |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04eb7338881909f3c430bb73f91d1 |
completed | April 16, 2026, 2:51 a.m. |
| PD | Predicate disambiguation | batch_69deda868d4481908f4bce1c64d2902a |
completed | April 15, 2026, 12:23 a.m. |
| PDg | Predicate description generation | batch_69dff7f3016c8190ac68d76e65e07af4 |
completed | April 15, 2026, 8:41 p.m. |
Created at: April 10, 2026, 4:14 a.m.