Triple
T28788934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burp Intruder |
E726896
|
entity |
| Predicate | detectsVulnerabilityType |
P38345
|
FINISHED |
| Object | injection flaws |
—
|
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: injection flaws | Statement: [Burp Intruder, detectsVulnerabilityType, injection flaws]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: detectsVulnerabilityType Context triple: [Burp Intruder, detectsVulnerabilityType, injection flaws]
-
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.
vulnerabilitySource
Indicates that one entity is the origin, cause, or contributing factor of another entity’s vulnerability or weakness.
-
D.
securityVulnerability
Indicates that an entity has a weakness or flaw that could be exploited to compromise its security.
-
E.
recognizesThreat
chosen
Indicates that an entity identifies or acknowledges another entity or situation as a potential danger or source of harm.
- 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_69f0319aabec81908368720196f69a35 |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f658ee40088190b71e1219407690d0 |
completed | May 2, 2026, 8:05 p.m. |
| PD | Predicate disambiguation | batch_69f65760fd3081908ffe014a5e2bf069 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 28, 2026, 6:22 a.m.