Triple

T14396136
Position Surface form Disambiguated ID Type / Status
Subject SAST E356952 entity
Predicate supportsStandard P1587 FINISHED
Object OWASP Top 10 E697168 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 Top 10 | Statement: [SAST, supportsStandard, OWASP Top 10]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: OWASP Top 10
Context triple: [SAST, supportsStandard, OWASP Top 10]
  • A. OWASP Top 10 protections chosen
    OWASP Top 10 protections are a widely recognized set of security controls and best practices designed to mitigate the most critical web application security risks identified by the Open Web Application Security Project.
  • B. OWASP
    OWASP is a global non-profit organization focused on improving the security of software through open-source projects, community-led initiatives, and educational resources.
  • C. VulnDB
    VulnDB is a comprehensive vulnerability database that catalogs security flaws and exposures to support assessment, remediation, and integration with security tools.
  • D. Checkmarx
    Checkmarx is a cybersecurity company specializing in application security testing solutions that help organizations identify and remediate vulnerabilities in their software code.
  • E. How to Break Web Software
    "How to Break Web Software" is a software testing book that focuses on systematically finding security and reliability flaws in web applications.
  • 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_69d827927c988190ad98bb0360981783 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de90826f908190b3969af9b7cf922f completed April 14, 2026, 7:07 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd551cbdb08190a9ea53e607f2555b completed May 8, 2026, 3:14 a.m.
Created at: April 10, 2026, 1:17 a.m.