Triple

T9932386
Position Surface form Disambiguated ID Type / Status
Subject Symantec E192676 entity
Predicate notableProduct P1448 FINISHED
Object Norton Security E563896 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: Norton Security | Statement: [Symantec, notableProduct, Norton Security]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Norton Security
Context triple: [Symantec, notableProduct, Norton Security]
  • A. Norton Antivirus chosen
    Norton Antivirus is a widely used commercial antivirus and security software suite designed to protect computers and devices from malware, viruses, and other online threats.
  • B. Norton Utilities
    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.
  • C. McAfee
    McAfee is a global cybersecurity company best known for its antivirus and digital security software for consumers and businesses.
  • D. Norton
    Norton is a residential suburb within the town of Runcorn in Cheshire, England.
  • E. Norton
    Norton is a town in Zimbabwe located near the Manyame River, known for its agricultural activities and proximity to the capital, Harare.
  • 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_69ca82dd978c8190947124ab0d3315ac completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb5b7897081909b28189aa57af250 completed April 2, 2026, 12:17 a.m.
NED1 Entity disambiguation (via context triple) batch_69d23d38c6748190a1c28c97f2a84f37 completed April 5, 2026, 10:45 a.m.
Created at: March 30, 2026, 8:43 p.m.