Triple
T20805488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Buras, Louisiana |
E512142
|
entity |
| Predicate | vulnerabilityTo |
P583
|
FINISHED |
| Object | hurricanes |
—
|
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: hurricanes | Statement: [Buras, Louisiana, vulnerabilityTo, hurricanes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: vulnerabilityTo Context triple: [Buras, Louisiana, vulnerabilityTo, hurricanes]
-
A.
susceptibleTo
chosen
Indicates that one entity is vulnerable or likely to be affected, harmed, or influenced by another entity or factor.
-
B.
vulnerabilityType
Indicates the specific kind or category of vulnerability associated with an entity or situation.
-
C.
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.
-
D.
vulnerabilitySource
Indicates that one entity is the origin, cause, or contributing factor of another entity’s vulnerability or weakness.
-
E.
associatedWithVulnerability
Indicates a relationship where an entity is linked to, affected by, or relevant to a specific vulnerability or security weakness.
- 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_69e0b4cc69f481908e98751e697b9df4 |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c2cf1cbc819092d92625dfb107d0 |
completed | April 21, 2026, 12:20 a.m. |
| PD | Predicate disambiguation | batch_69e5c99ca55481908e8d434fa901cfd6 |
completed | April 20, 2026, 6:37 a.m. |
Created at: April 16, 2026, 12:40 p.m.