Triple
T21226590
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Network Slice Instance |
E523098
|
entity |
| Predicate | managedBy |
P86
|
FINISHED |
| Object | Network Slice Management and Orchestration |
—
|
NE NERFINISHED |
How this triple was built (3 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: Network Slice Management and Orchestration | Statement: [Network Slice Instance, managedBy, Network Slice Management and Orchestration]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Network Slice Management and Orchestration Context triple: [Network Slice Instance, managedBy, Network Slice Management and Orchestration]
-
A.
Network Slice Selection Function
The Network Slice Selection Function (NSSF) is a 5G core network function that determines and assigns the appropriate network slice for user equipment based on subscription, service requirements, and network policies.
-
B.
Network Slice Instance
A Network Slice Instance is a logically isolated, end-to-end 5G network partition tailored to specific service or customer requirements, providing dedicated resources and performance characteristics.
-
C.
Next Generation Network architectures
Next Generation Network architectures are advanced telecommunications frameworks that integrate voice, data, and multimedia services over a unified, packet-based IP infrastructure to enable flexible, scalable, and service-agnostic communication.
-
D.
Access and Mobility Management Function
The Access and Mobility Management Function (AMF) is a key 5G core network control-plane function responsible for user equipment registration, connection and mobility management, and access authentication.
-
E.
Network-in-Network architecture
Network-in-Network architecture is a convolutional neural network design that replaces traditional linear convolution layers with micro multilayer perceptrons (MLPs) to enhance feature abstraction and model expressiveness.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Network Slice Management and Orchestration Target entity description: Network Slice Management and Orchestration is a 5G network function framework responsible for the end-to-end lifecycle management, coordination, and automation of network slice instances across underlying infrastructure and services.
-
A.
Network Slice Selection Function
The Network Slice Selection Function (NSSF) is a 5G core network function that determines and assigns the appropriate network slice for user equipment based on subscription, service requirements, and network policies.
-
B.
Network Slice Instance
A Network Slice Instance is a logically isolated, end-to-end 5G network partition tailored to specific service or customer requirements, providing dedicated resources and performance characteristics.
-
C.
Next Generation Network architectures
Next Generation Network architectures are advanced telecommunications frameworks that integrate voice, data, and multimedia services over a unified, packet-based IP infrastructure to enable flexible, scalable, and service-agnostic communication.
-
D.
Access and Mobility Management Function
The Access and Mobility Management Function (AMF) is a key 5G core network control-plane function responsible for user equipment registration, connection and mobility management, and access authentication.
-
E.
Network-in-Network architecture
Network-in-Network architecture is a convolutional neural network design that replaces traditional linear convolution layers with micro multilayer perceptrons (MLPs) to enhance feature abstraction and model expressiveness.
- F. None of above. chosen
Provenance (2 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_69e0b512ad94819087942b2ed925185f |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e734ab3f6c819083e277ea1c33134e |
completed | April 21, 2026, 8:26 a.m. |
Created at: April 16, 2026, 3:44 p.m.