Triple

T4980097
Position Surface form Disambiguated ID Type / Status
Subject Wireshark E111861 entity
Predicate usesLibrary P4791 FINISHED
Object libpcap E484050 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: libpcap | Statement: [Wireshark, usesLibrary, libpcap]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: libpcap
Context triple: [Wireshark, usesLibrary, libpcap]
  • A. libpcap chosen
    libpcap is a widely used packet capture library and file format for recording and analyzing network traffic across various tools and platforms.
  • B. WinPcap
    WinPcap is a Windows packet capture and network monitoring library that provides low-level network access for tools like Wireshark.
  • C. Npcap
    Npcap is a high-performance packet capture and network monitoring library for Windows, commonly used by tools like Wireshark for low-level network traffic analysis.
  • D. Wireshark
    Wireshark is a widely used open-source network protocol analyzer that captures and interactively inspects traffic on computer networks for troubleshooting, analysis, and security auditing.
  • E. 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.
  • 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_69bd441adc208190b70a033a0741d01e completed March 20, 2026, 12:56 p.m.
NER Named-entity recognition batch_69bd7251b7648190bbb0acf0b9148ae6 completed March 20, 2026, 4:14 p.m.
NED1 Entity disambiguation (via context triple) batch_69be924befc08190a077adca99fb4b86 completed March 21, 2026, 12:42 p.m.
Created at: March 20, 2026, 1:33 p.m.