Triple

T12367430
Position Surface form Disambiguated ID Type / Status
Subject Delay-Tolerant Networking Research Group E294907 entity
Predicate relatedTo P37 FINISHED
Object Delay-Tolerant Networking architecture
Delay-Tolerant Networking architecture is a network design framework that enables reliable data communication in environments with intermittent connectivity, long delays, or high error rates, such as space, rural, or disaster-response networks.
E294907 NE FINISHED

How this triple was built (4 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: Delay-Tolerant Networking architecture | Statement: [Delay-Tolerant Networking Research Group, relatedTo, Delay-Tolerant Networking architecture]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Delay-Tolerant Networking architecture
Context triple: [Delay-Tolerant Networking Research Group, relatedTo, Delay-Tolerant Networking architecture]
  • A. Delay-Tolerant Networking Research Group
    The Delay-Tolerant Networking Research Group is an IRTF working group that develops architectures and protocols for communication in challenged or intermittently connected networks, such as deep space, disaster, or mobile ad hoc environments.
  • B. 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.
  • C. Time-Sensitive Networking
    Time-Sensitive Networking is a set of IEEE 802 Ethernet standards that enable deterministic, low-latency, and highly reliable communication for real-time applications such as industrial automation, automotive, and professional audio/video.
  • D. Time-Triggered Architecture
    Time-Triggered Architecture is a deterministic, time-driven computing and communication framework used in safety-critical real-time systems to ensure predictable and reliable operation.
  • E. Communication Nets: Stochastic Message Flow and Delay
    "Communication Nets: Stochastic Message Flow and Delay" is a foundational book in queueing theory and computer networking that rigorously analyzes message traffic and delays in communication networks.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Delay-Tolerant Networking architecture
Triple: [Delay-Tolerant Networking Research Group, relatedTo, Delay-Tolerant Networking architecture]
Generated description
Delay-Tolerant Networking architecture is a network design framework that enables reliable data communication in environments with intermittent connectivity, long delays, or high error rates, such as space, rural, or disaster-response networks.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Delay-Tolerant Networking architecture
Target entity description: Delay-Tolerant Networking architecture is a network design framework that enables reliable data communication in environments with intermittent connectivity, long delays, or high error rates, such as space, rural, or disaster-response networks.
  • A. Delay-Tolerant Networking Research Group chosen
    The Delay-Tolerant Networking Research Group is an IRTF working group that develops architectures and protocols for communication in challenged or intermittently connected networks, such as deep space, disaster, or mobile ad hoc environments.
  • B. 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.
  • C. Time-Sensitive Networking
    Time-Sensitive Networking is a set of IEEE 802 Ethernet standards that enable deterministic, low-latency, and highly reliable communication for real-time applications such as industrial automation, automotive, and professional audio/video.
  • D. Time-Triggered Architecture
    Time-Triggered Architecture is a deterministic, time-driven computing and communication framework used in safety-critical real-time systems to ensure predictable and reliable operation.
  • E. Communication Nets: Stochastic Message Flow and Delay
    "Communication Nets: Stochastic Message Flow and Delay" is a foundational book in queueing theory and computer networking that rigorously analyzes message traffic and delays in communication networks.
  • F. None of above.

Provenance (5 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_69d6ab6d8a4081908636601e69ddf262 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93fa502988190ba170dee90d9f394 completed April 10, 2026, 6:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f62abdad1c8190b083791d60138f2a completed May 2, 2026, 4:47 p.m.
NEDg Description generation batch_69f62be4de888190aac94d441748d295 completed May 2, 2026, 4:52 p.m.
NED2 Entity disambiguation (via description) batch_69f62d4d0b8881908aa6b67db7d14609 completed May 2, 2026, 4:58 p.m.
Created at: April 8, 2026, 9:54 p.m.