Triple

T9932417
Position Surface form Disambiguated ID Type / Status
Subject Symantec E192676 entity
Predicate notableBrand P1500 FINISHED
Object Norton
Norton is a widely used cybersecurity brand best known for its antivirus and internet security software products.
 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: [Symantec, notableBrand, Norton]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Norton
Context triple: [Symantec, notableBrand, Norton]
  • A. 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.
  • B. Norton
    Norton is a surname of English origin borne by numerous notable individuals across fields such as literature, politics, and the arts.
  • C. Norton
    Norton is a residential suburb within the town of Runcorn in Cheshire, England.
  • D. Norton
    Norton is a town in Zimbabwe located near the Manyame River, known for its agricultural activities and proximity to the capital, Harare.
  • E. Norton
    Norton is a town within the Teesside urban area in North East England, known for its historic high street and village green.
  • 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: [Symantec, notableBrand, Norton]
Generated description
Norton is a widely used cybersecurity brand best known for its antivirus and internet security software products.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Norton
Target entity description: Norton is a widely used cybersecurity brand best known for its antivirus and internet security software products.
  • 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 surname of English origin borne by numerous notable individuals across fields such as literature, politics, and the arts.
  • 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 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_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_69d228d1620c8190ac7125b268dd6832 completed April 5, 2026, 9:18 a.m.
NEDg Description generation batch_69d22c3a6fc0819083a376736325a04e completed April 5, 2026, 9:32 a.m.
NED2 Entity disambiguation (via description) batch_69d22cabf39881908f45667751384df5 completed April 5, 2026, 9:34 a.m.
Created at: March 30, 2026, 8:43 p.m.