Triple
T577482
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hellman & Friedman |
E13786
|
entity |
| Predicate | notableInvestment |
P3488
|
FINISHED |
| Object |
Verisure
Verisure is a leading European provider of professionally monitored home and business security alarm systems.
|
E72310
|
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: Verisure | Statement: [Hellman & Friedman, notableInvestment, Verisure]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Verisure Context triple: [Hellman & Friedman, notableInvestment, Verisure]
-
A.
Honeywell
Honeywell is a multinational conglomerate best known for its aerospace systems, building technologies, performance materials, and industrial automation products.
-
B.
Fortive
Fortive is an American diversified industrial technology company that owns and operates a portfolio of measurement, automation, and industrial solutions businesses.
-
C.
Duo Security
Duo Security is a cybersecurity company best known for its cloud-based multi-factor authentication and zero-trust access solutions.
-
D.
Tandberg
Tandberg is a Norwegian company best known for its video conferencing and telepresence solutions, which became part of Cisco Systems after its acquisition.
-
E.
Lockit
Lockit is the corrupt jailer and one of the main antagonists in John Gay's satirical ballad opera "The Beggar's Opera."
- 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: Verisure Triple: [Hellman & Friedman, notableInvestment, Verisure]
Generated description
Verisure is a leading European provider of professionally monitored home and business security alarm systems.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Verisure Target entity description: Verisure is a leading European provider of professionally monitored home and business security alarm systems.
-
A.
Honeywell
Honeywell is a multinational conglomerate best known for its aerospace systems, building technologies, performance materials, and industrial automation products.
-
B.
Fortive
Fortive is an American diversified industrial technology company that owns and operates a portfolio of measurement, automation, and industrial solutions businesses.
-
C.
Duo Security
Duo Security is a cybersecurity company best known for its cloud-based multi-factor authentication and zero-trust access solutions.
-
D.
Tandberg
Tandberg is a Norwegian company best known for its video conferencing and telepresence solutions, which became part of Cisco Systems after its acquisition.
-
E.
Lockit
Lockit is the corrupt jailer and one of the main antagonists in John Gay's satirical ballad opera "The Beggar's Opera."
- 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_69a4933fa4d88190a7949cc83c08c5c1 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49d2a5f5481908bb9a71ff0f534d4 |
completed | March 1, 2026, 8:10 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a501bfb6408190bf7e1f462f39723d |
completed | March 2, 2026, 3:19 a.m. |
| NEDg | Description generation | batch_69a5026c35408190ab22dab86c673e0f |
completed | March 2, 2026, 3:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69a5063ad6b481909537a97e6a81eaa4 |
completed | March 2, 2026, 3:38 a.m. |
Created at: March 1, 2026, 7:33 p.m.