Triple
T21322579
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 3GPP TS 24.010 |
E525656
|
entity |
| Predicate | usesReferenceModel |
P37433
|
FINISHED |
| Object | OSI layer model |
—
|
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: OSI layer model | Statement: [3GPP TS 24.010, usesReferenceModel, OSI layer model]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesReferenceModel Context triple: [3GPP TS 24.010, usesReferenceModel, OSI layer model]
-
A.
usesReferenceObjects
Indicates that an entity performs an action or makes a determination by relying on one or more other entities as reference points or benchmarks.
-
B.
useOfModel
chosen
Indicates that one entity employs, applies, or relies on a particular model for a specific purpose or task.
-
C.
usedByModel
Indicates that something (such as a resource, method, or component) is utilized or consumed by a particular model.
-
D.
usesModelsType
Indicates that one entity employs or relies on a specific type or category of models in its operation or behavior.
-
E.
isReferencedIn
Indicates that one entity is cited, mentioned, or otherwise referred to within another entity.
- 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_69e0b51ad810819098c12392c8e55f6c |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e77ed355cc8190a305c1c48117fb9e |
completed | April 21, 2026, 1:42 p.m. |
| PD | Predicate disambiguation | batch_69e6161feea4819091d13bb003363279 |
completed | April 20, 2026, 12:03 p.m. |
Created at: April 16, 2026, 4:40 p.m.