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.