Triple
T8248082
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Offensive Security |
E192895
|
entity |
| Predicate | assessmentEmphasis |
P81182
|
FINISHED |
| Object | real-world scenarios |
—
|
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: real-world scenarios | Statement: [Offensive Security, assessmentEmphasis, real-world scenarios]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: assessmentEmphasis Context triple: [Offensive Security, assessmentEmphasis, real-world scenarios]
-
A.
assessmentBasis
Indicates the underlying criteria, evidence, or method used as the foundation for making an assessment or evaluation between entities.
-
B.
assessmentLevel
Indicates the degree, rating, or intensity assigned to an evaluation or judgment of something.
-
C.
assessment
Indicates an evaluation or judgment made about an entity’s quality, performance, or characteristics.
-
D.
requiresAssessmentOf
Indicates that one entity necessitates an evaluation, review, or judgment to be performed on another entity before proceeding or fulfilling a condition.
-
E.
assessmentMethod
Indicates the method or procedure used to evaluate, measure, or judge something.
- 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_69ca82de7b8c81908d8106f8a53cff9b |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7875318c819095f971ba513c54fd |
completed | March 31, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69cb36b437e881909958591357e83b9d |
completed | March 31, 2026, 2:51 a.m. |
| PDg | Predicate description generation | batch_69cb447c146081909decf97bbd26c496 |
completed | March 31, 2026, 3:50 a.m. |
Created at: March 30, 2026, 5:48 p.m.