Triple

T2114161
Position Surface form Disambiguated ID Type / Status
Subject Noise protocol framework E42567 entity
Predicate usedBy P260 FINISHED
Object WireGuard E233811 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: WireGuard | Statement: [Noise protocol framework, usedBy, WireGuard]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: WireGuard
Context triple: [Noise protocol framework, usedBy, WireGuard]
  • A. WireGuard VPN protocol chosen
    WireGuard VPN protocol is a modern, lightweight, and high-performance virtual private network protocol focused on simplicity and strong cryptographic security.
  • B. OpenVPN
    OpenVPN is an open-source virtual private network (VPN) solution that enables secure, encrypted connections over the internet for remote access and site-to-site networking.
  • C. Teredo
    Teredo is a tunneling protocol that enables IPv6 connectivity for devices on IPv4 networks, particularly those behind NAT.
  • D. TUN
    TUN is the three-letter ISO 3166-1 alpha-3 country code assigned to Tunisia.
  • E. IKEv2
    IKEv2 is a modern key management and security association protocol used to establish and maintain secure VPN connections in IPsec-based networks.
  • 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_69a8871040f08190aac2e2d0ab6b47ad completed March 4, 2026, 7:25 p.m.
NER Named-entity recognition batch_69abbb05b51c81908a78c816f492c45c completed March 7, 2026, 5:43 a.m.
NED1 Entity disambiguation (via context triple) batch_69ae5194abec8190aab8b7a9ef98da92 completed March 9, 2026, 4:50 a.m.
Created at: March 4, 2026, 7:43 p.m.