Triple
T300594
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RESTCONF |
E6188
|
entity |
| Predicate | usesDataModel |
P535
|
FINISHED |
| Object | YANG |
—
|
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: YANG | Statement: [RESTCONF, usesDataModel, YANG]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesDataModel Context triple: [RESTCONF, usesDataModel, YANG]
-
A.
dataModel
chosen
Indicates a relationship where an entity defines, uses, or is structured according to a specific data model or schema.
-
B.
usesBusinessModel
Indicates that one entity operates according to, or applies in practice, the business model defined or provided by another entity.
-
C.
dataUse
Indicates how data is intended to be accessed, processed, or applied within a particular context or activity.
-
D.
usesAccessMethod
Indicates that one entity employs or relies on a particular access method to reach, interact with, or retrieve another entity or resource.
-
E.
actualUse
Indicates that an entity is currently being used or utilized in practice, as opposed to being merely available, planned, or potential.
- 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_69a2e79114b081909490b3bf5a5dbb51 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2ea2fba548190a5aeb1597dca96bd |
completed | Feb. 28, 2026, 1:14 p.m. |
| PD | Predicate disambiguation | batch_69a2e93aff048190a633c8ae2b76a41f |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:06 p.m.