Triple

T8248849
Position Surface form Disambiguated ID Type / Status
Subject BeEF E192906 entity
Predicate canIntegrateWith P48644 FINISHED
Object Metasploit Framework E192897 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: Metasploit Framework | Statement: [BeEF, canIntegrateWith, Metasploit Framework]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Metasploit Framework
Context triple: [BeEF, canIntegrateWith, Metasploit Framework]
  • A. Metasploit Framework chosen
    Metasploit Framework is an open-source penetration testing platform widely used for developing, testing, and executing exploits against remote targets.
  • B. Social-Engineer Toolkit
    Social-Engineer Toolkit is an open-source penetration testing framework focused on automating and simulating social engineering attacks such as phishing, credential harvesting, and other human-targeted exploits.
  • C. BeEF
    BeEF (Browser Exploitation Framework) is a penetration testing tool focused on exploiting web browsers to assess and demonstrate client-side security vulnerabilities.
  • D. Nessus
    Nessus is a centaur in Greek mythology best known for his role in the death of Heracles after deceitfully causing the poisoned garment incident.
  • 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_69ca82de7b8c81908d8106f8a53cff9b completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb78c6b3c48190a3ecebf449766124 completed March 31, 2026, 7:33 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd353888208190941d1c0b7b911cdd completed April 1, 2026, 3:09 p.m.
Created at: March 30, 2026, 5:48 p.m.