Triple

T4554434
Position Surface form Disambiguated ID Type / Status
Subject Jetpack E120446 entity
Predicate hasComponent P35 FINISHED
Object Jetpack Scan E192908 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: Jetpack Scan | Statement: [Jetpack, hasComponent, Jetpack Scan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jetpack Scan
Context triple: [Jetpack, hasComponent, Jetpack Scan]
  • A. 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.
  • B. Tenable
    Tenable is a British daytime television quiz show, hosted by Warwick Davis, in which teams of contestants attempt to complete top-ten lists on a variety of topics.
  • C. Checkmarx
    Checkmarx is a cybersecurity company specializing in application security testing solutions that help organizations identify and remediate vulnerabilities in their software code.
  • D. OpenVAS chosen
    OpenVAS is an open-source vulnerability scanning and management framework used to assess and improve the security of computer networks and systems.
  • E. SATAN security scanner
    SATAN security scanner is an early network vulnerability assessment tool that automated the process of discovering and reporting security weaknesses on Unix systems.
  • 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_69bd4636f1648190a701445c2fcd9c17 completed March 20, 2026, 1:05 p.m.
NER Named-entity recognition batch_69bd58127ed08190a04962a43afb888b completed March 20, 2026, 2:22 p.m.
NED1 Entity disambiguation (via context triple) batch_69bdc575e3388190ac95b9e0537fb701 completed March 20, 2026, 10:08 p.m.
Created at: March 20, 2026, 1:09 p.m.