Triple

T23423777
Position Surface form Disambiguated ID Type / Status
Subject Norton Utilities E560735 entity
Predicate component P35 FINISHED
Object Norton System Information NE NERFINISHED

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: Norton System Information | Statement: [Norton Utilities, component, Norton System Information]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Norton System Information
Context triple: [Norton Utilities, component, Norton System Information]
  • A. Norton Utilities chosen
    Norton Utilities is a software suite of diagnostic and optimization tools for DOS and Windows computers, originally developed by Peter Norton to help maintain and repair PC systems.
  • B. Norton
    Norton is a dark-skinned American grape variety, historically significant in Midwestern and Eastern U.S. winemaking for producing deeply colored, full-bodied red wines with notable disease resistance.
  • C. Norton
    Norton is a town within the Teesside urban area in North East England, known for its historic high street and village green.
  • D. Norton
    Norton is a residential suburb within the town of Runcorn in Cheshire, England.
  • E. Norton
    Norton is a well-known cybersecurity and antivirus software brand that provides protection solutions for personal computers, mobile devices, and online activities.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e2454cb1108190ab21ada5411a7146 completed April 17, 2026, 2:35 p.m.
NER Named-entity recognition batch_69f1a54838fc8190a3205ca72daaf107 completed April 29, 2026, 6:29 a.m.
Created at: April 17, 2026, 5:47 p.m.