Triple

T9963095
Position Surface form Disambiguated ID Type / Status
Subject OWASP ZAP E195615 entity
Predicate fullName P16 FINISHED
Object OWASP Zed Attack Proxy E195615 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: OWASP Zed Attack Proxy | Statement: [OWASP ZAP, fullName, OWASP Zed Attack Proxy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: OWASP Zed Attack Proxy
Context triple: [OWASP ZAP, fullName, OWASP Zed Attack Proxy]
  • A. OWASP ZAP chosen
    OWASP ZAP (Zed Attack Proxy) is an open-source web application security testing tool used to find vulnerabilities in web applications.
  • B. Burp Suite
    Burp Suite is a popular integrated platform for web application security testing, widely used by penetration testers to identify and exploit vulnerabilities.
  • C. Burp Intruder
    Burp Intruder is a powerful web application security testing tool within Burp Suite that automates customized attacks to discover vulnerabilities such as injection flaws and authentication weaknesses.
  • D. BeEF
    BeEF (Browser Exploitation Framework) is a penetration testing tool focused on exploiting web browsers to assess and demonstrate client-side security vulnerabilities.
  • 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_69ca82ebd1288190912f9e4482d1fa35 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb718cd588190a4aac48220deddec completed April 2, 2026, 12:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69d23d993404819089c9a71d03721e0b completed April 5, 2026, 10:46 a.m.
Created at: March 30, 2026, 8:47 p.m.