Triple
T33555893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CMS |
E859471
|
entity |
| Predicate | userModel |
P176883
|
FINISHED |
| Object | single user per virtual machine |
—
|
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: single user per virtual machine | Statement: [CMS, userModel, single user per virtual machine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: userModel Context triple: [CMS, userModel, single user per virtual machine]
-
A.
userSystem
Indicates a relationship where a user interacts with, accesses, or is associated with a particular system.
-
B.
userBase
Indicates that one entity serves as the primary or foundational group of users associated with another entity.
-
C.
user
Indicates a relationship where an entity actively operates, controls, or interacts with another entity, typically as the primary agent or consumer of its function.
-
D.
studentModel
Indicates that one entity serves as a model or example for a student in the context of learning or education.
-
E.
governingBodyUser
Indicates that a user acts as a governing or decision-making authority for a particular entity or organization.
- 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_69f3497b2b68819093207971b5e13dc8 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6f8164698819090c1b471f1caa4c6 |
completed | May 3, 2026, 7:24 a.m. |
| PD | Predicate disambiguation | batch_69f6f6632dfc8190af85e258c8519207 |
completed | May 3, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69f6f70b0ca081908b24a98937e6ef66 |
completed | May 3, 2026, 7:19 a.m. |
Created at: May 1, 2026, 1:40 a.m.