Triple

T14423098
Position Surface form Disambiguated ID Type / Status
Subject Gen Digital E357630 entity
Predicate hasBrand P1500 FINISHED
Object Norton
Norton is a well-known cybersecurity brand offering antivirus and internet security software and services for consumers and businesses.
 E662032 NE FINISHED

How this triple was built (4 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 | Statement: [Gen Digital, hasBrand, Norton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Norton
Context triple: [Gen Digital, hasBrand, Norton]
  • A. Norton
    Norton is a surname of English origin borne by numerous notable individuals across fields such as literature, politics, and the arts.
  • B. Norton
    Norton is a small town in Bristol County, southeastern Massachusetts, known for being home to Wheaton College and several scenic ponds and conservation areas.
  • C. Norton
    Norton is a historic British motorcycle manufacturer renowned for its success in mid-20th-century road racing and the Isle of Man TT.
  • D. Norton
    Norton is a town within the Teesside urban area in North East England, known for its historic high street and village green.
  • E. Norton
    Norton is a village in Gloucestershire, England, situated near the River Chelt and close to the town of Cheltenham.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Norton
Triple: [Gen Digital, hasBrand, Norton]
Generated description
Norton is a well-known cybersecurity brand offering antivirus and internet security software and services for consumers and businesses.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Norton
Target entity description: Norton is a well-known cybersecurity brand offering antivirus and internet security software and services for consumers and businesses.
  • A. Norton chosen
    Norton is a well-known cybersecurity and antivirus software brand that provides protection solutions for personal computers, mobile devices, and online activities.
  • B. Norton
    Norton is a historic British motorcycle manufacturer renowned for its success in mid-20th-century road racing and the Isle of Man TT.
  • C. Norton
    Norton is a surname of English origin borne by numerous notable individuals across fields such as literature, politics, and the arts.
  • D. Norton
    Norton is a town within the Teesside urban area in North East England, known for its historic high street and village green.
  • E. Norton
    Norton is a small town in Bristol County, southeastern Massachusetts, known for being home to Wheaton College and several scenic ponds and conservation areas.
  • F. None of above.

Provenance (5 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_69d82793421c8190861eb0e673b085de completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de91102c3c81908f571a1fff3bdd47 completed April 14, 2026, 7:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd5bcd2a908190ad7d5ebf11b41551 completed May 8, 2026, 3:43 a.m.
NEDg Description generation batch_69fd5d585cc08190908bc5f9b8abdb82 completed May 8, 2026, 3:49 a.m.
NED2 Entity disambiguation (via description) batch_69fd5e0bbd6c8190b14039b3335692c7 completed May 8, 2026, 3:52 a.m.
Created at: April 10, 2026, 1:18 a.m.