Triple

T10157783
Position Surface form Disambiguated ID Type / Status
Subject RFC 959 E233815 entity
Predicate operatesOver P3695 FINISHED
Object TCP/IP networks E1063 NE 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: TCP/IP networks | Statement: [RFC 959, operatesOver, TCP/IP networks]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: TCP/IP networks
Context triple: [RFC 959, operatesOver, TCP/IP networks]
  • A. TCP/IP chosen
    TCP/IP is the fundamental communication protocol suite that enables data transmission and networking across the internet and most modern computer networks.
  • B. Computer Networks
    Computer Networks is a widely used textbook that provides a comprehensive introduction to the principles, architectures, and protocols underlying modern computer networking.
  • C. Data and Computer Communications
    Data and Computer Communications is a widely used textbook by William Stallings that provides a comprehensive introduction to data communications, networking, and computer communication protocols.
  • D. Internet Protocol
    Internet Protocol is the core networking protocol that defines how data packets are addressed and routed across interconnected computer networks, forming the foundation of the modern internet.
  • 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.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69ca848e80748190b91d1e04d35512c7 completed March 30, 2026, 2:11 p.m.
NER Named-entity recognition batch_69cdec5507f08190b47f797bacd5640c completed April 2, 2026, 4:11 a.m.
NED1 Entity disambiguation (via context triple) batch_69d300acae608190891d8f55c3d5102b completed April 6, 2026, 12:39 a.m.
Created at: March 30, 2026, 9:09 p.m.