Triple
T9932420
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Symantec |
E192676
|
entity |
| Predicate | hasCompetitor |
P1375
|
FINISHED |
| Object |
Kaspersky Lab
Kaspersky Lab is a Russian cybersecurity and anti-virus company known for developing security software and threat intelligence solutions used worldwide.
|
E831102
|
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: Kaspersky Lab | Statement: [Symantec, hasCompetitor, Kaspersky Lab]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Kaspersky Lab Context triple: [Symantec, hasCompetitor, Kaspersky Lab]
-
A.
Trend Micro
Trend Micro is a global cybersecurity company known for its antivirus, cloud security, and enterprise threat protection solutions.
-
B.
McAfee
McAfee is a global cybersecurity company best known for its antivirus and digital security software for consumers and businesses.
-
C.
Comodo Group
Comodo Group is a cybersecurity company best known for its SSL certificates, internet security software, and secure web browser products.
-
D.
Symantec
Symantec is a cybersecurity and software company best known for its Norton antivirus products and enterprise security solutions.
-
E.
Avast Software s.r.o.
Avast Software s.r.o. is a Czech cybersecurity company best known for its antivirus and internet security products for consumers and businesses worldwide.
- 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: Kaspersky Lab Triple: [Symantec, hasCompetitor, Kaspersky Lab]
Generated description
Kaspersky Lab is a Russian cybersecurity and anti-virus company known for developing security software and threat intelligence solutions used worldwide.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Kaspersky Lab Target entity description: Kaspersky Lab is a Russian cybersecurity and anti-virus company known for developing security software and threat intelligence solutions used worldwide.
-
A.
Trend Micro
Trend Micro is a global cybersecurity company known for its antivirus, cloud security, and enterprise threat protection solutions.
-
B.
McAfee
McAfee is a global cybersecurity company best known for its antivirus and digital security software for consumers and businesses.
-
C.
Comodo Group
Comodo Group is a cybersecurity company best known for its SSL certificates, internet security software, and secure web browser products.
-
D.
Symantec
Symantec is a cybersecurity and software company best known for its Norton antivirus products and enterprise security solutions.
-
E.
Avast Software s.r.o.
Avast Software s.r.o. is a Czech cybersecurity company best known for its antivirus and internet security products for consumers and businesses worldwide.
- F. None of above. chosen
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.