Triple
T9932387
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Symantec |
E192676
|
entity |
| Predicate | notableProduct |
P1448
|
FINISHED |
| Object | Norton 360 |
E662032
|
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 360 | Statement: [Symantec, notableProduct, Norton 360]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Norton 360 Context triple: [Symantec, notableProduct, Norton 360]
-
A.
Norton Antivirus
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 town in Zimbabwe located near the Manyame River, known for its agricultural activities and proximity to the capital, Harare.
-
E.
Norton
chosen
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 (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_69d2578e92f08190ba53f943f3da2166 |
completed | April 5, 2026, 12:37 p.m. |
Created at: March 30, 2026, 8:43 p.m.