Triple

T19352265
Position Surface form Disambiguated ID Type / Status
Subject WinPcap E484051 entity
Predicate usedBy P260 FINISHED
Object Snort NE NERFINISHED

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: Snort | Statement: [WinPcap, usedBy, Snort]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Snort
Context triple: [WinPcap, usedBy, Snort]
  • A. Snort chosen
    Snort is an open-source network intrusion detection and prevention system (NIDS/NIPS) widely used for real-time traffic analysis and packet logging.
  • B. Suricata
    Suricata is an open-source, high-performance network threat detection engine that provides intrusion detection, intrusion prevention, and network security monitoring capabilities.
  • C. Ettercap
    Ettercap is a network security tool used for sniffing, intercepting, and manipulating traffic on local area networks, commonly employed for man-in-the-middle attacks and protocol analysis.
  • D. NIDS
    NIDS is Japan’s principal defense think tank and research institute, providing strategic studies, policy analysis, and military history research for the Ministry of Defense.
  • E. IronPort
    IronPort is an email and web security company best known for its high-performance anti-spam and anti-malware gateway appliances, later acquired by Cisco Systems.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d8e8d244f8819080eb1f3491300db2 completed April 10, 2026, 12:10 p.m.
NER Named-entity recognition batch_69e61905b16881909ab0e932bb9a0cda completed April 20, 2026, 12:16 p.m.
Created at: April 10, 2026, 1:34 p.m.