Triple

T22488044
Position Surface form Disambiguated ID Type / Status
Subject Roger Dingledine E555942 entity
Predicate notableWork P4 FINISHED
Object Onion routing implementations in Tor 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: Onion routing implementations in Tor | Statement: [Roger Dingledine, notableWork, Onion routing implementations in Tor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Onion routing implementations in Tor
Context triple: [Roger Dingledine, notableWork, Onion routing implementations in Tor]
  • A. Pluggable transports
    Pluggable transports are modular protocols used by Tor to disguise and obfuscate network traffic, helping users circumvent censorship and traffic analysis.
  • B. Onion services
    Onion services are anonymous, end-to-end encrypted network services accessible only through the Tor network, designed to protect the privacy and location of both users and service operators.
  • C. The Tor Project
    The Tor Project is a nonprofit organization that develops and maintains privacy-focused tools—most notably the Tor anonymity network—to enable secure, uncensored communication online.
  • D. 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.
  • E. The Secure Shell (SSH) Transport Layer Protocol
    The Secure Shell (SSH) Transport Layer Protocol is the core low-level component of SSH that provides secure, encrypted, and integrity-protected communication over an insecure network, forming the foundation for higher-level SSH services.
  • 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: Onion routing implementations in Tor
Target entity description: Onion routing implementations in Tor are the core software mechanisms that enable Tor’s anonymous communication network by encrypting and routing internet traffic through multiple volunteer-operated relays.
  • A. Pluggable transports
    Pluggable transports are modular protocols used by Tor to disguise and obfuscate network traffic, helping users circumvent censorship and traffic analysis.
  • B. Onion services
    Onion services are anonymous, end-to-end encrypted network services accessible only through the Tor network, designed to protect the privacy and location of both users and service operators.
  • C. The Tor Project
    The Tor Project is a nonprofit organization that develops and maintains privacy-focused tools—most notably the Tor anonymity network—to enable secure, uncensored communication online.
  • D. 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.
  • E. The Secure Shell (SSH) Transport Layer Protocol
    The Secure Shell (SSH) Transport Layer Protocol is the core low-level component of SSH that provides secure, encrypted, and integrity-protected communication over an insecure network, forming the foundation for higher-level SSH services.
  • 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_69e11e53897c819088863779f8c50bb0 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15c3e73108190be5ca89ea96a85e4 completed April 29, 2026, 1:17 a.m.
Created at: April 16, 2026, 8:49 p.m.