Triple
T11656366
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SQL Server Authentication |
E277020
|
entity |
| Predicate | credentialScope |
P42519
|
FINISHED |
| Object | SQL Server instance level |
—
|
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: SQL Server instance level | Statement: [SQL Server Authentication, credentialScope, SQL Server instance level]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: credentialScope Context triple: [SQL Server Authentication, credentialScope, SQL Server instance level]
-
A.
securityScope
Indicates the range or extent of protection, permissions, or access control that applies within a given security context.
-
B.
accessScope
chosen
Indicates the extent or boundaries of access that one entity has to another entity or resource.
-
C.
organizationalScope
Indicates the range or extent of responsibility, authority, or applicability that an action, policy, or relationship has within an organization or its sub-units.
-
D.
scopeClaim
Indicates that a claim or statement applies within a specified scope, context, or boundary.
-
E.
identificationScope
Indicates the contextual boundary or extent within which an entity is uniquely identified or recognized.
- 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_69d6aafbb3c081908a9cdb4ecb8d981d |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a3d0331481909682b2e504e4c9a0 |
completed | April 10, 2026, 7:16 a.m. |
| PD | Predicate disambiguation | batch_69d85ddc780481909a3bc63832fe2bd2 |
completed | April 10, 2026, 2:18 a.m. |
Created at: April 8, 2026, 9:39 p.m.