Triple
T14388765
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samsung Knox |
E356788
|
entity |
| Predicate | component |
P35
|
FINISHED |
| Object |
Knox Manage
Knox Manage is Samsung’s cloud-based enterprise mobility management (EMM) solution for centrally configuring, securing, and managing fleets of mobile devices.
|
E1097893
|
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: Knox Manage | Statement: [Samsung Knox, component, Knox Manage]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Knox Manage Context triple: [Samsung Knox, component, Knox Manage]
-
A.
Kanmu
Kanmu was a powerful Japanese emperor of the late 8th and early 9th centuries best known for relocating the capital to Heian-kyō, laying the foundations of the Heian period.
-
B.
Kennex
Kennex is a surname most notably associated with the fictional detective John Kennex from the science fiction television series "Almost Human."
-
C.
Knox-Shaw
Knox-Shaw is a British surname most notably associated with astronomer Harold Knox-Shaw.
-
D.
Keepit Dam
Keepit Dam is a major water storage and irrigation dam located on the Namoi River in New South Wales, Australia.
-
E.
KNO
KNO is the IATA airport code for Kualanamu International Airport serving Medan and the surrounding region in North Sumatra, Indonesia.
- 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: Knox Manage Triple: [Samsung Knox, component, Knox Manage]
Generated description
Knox Manage is Samsung’s cloud-based enterprise mobility management (EMM) solution for centrally configuring, securing, and managing fleets of mobile devices.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Knox Manage Target entity description: Knox Manage is Samsung’s cloud-based enterprise mobility management (EMM) solution for centrally configuring, securing, and managing fleets of mobile devices.
-
A.
Kanmu
Kanmu was a powerful Japanese emperor of the late 8th and early 9th centuries best known for relocating the capital to Heian-kyō, laying the foundations of the Heian period.
-
B.
Kennex
Kennex is a surname most notably associated with the fictional detective John Kennex from the science fiction television series "Almost Human."
-
C.
Knox-Shaw
Knox-Shaw is a British surname most notably associated with astronomer Harold Knox-Shaw.
-
D.
Keepit Dam
Keepit Dam is a major water storage and irrigation dam located on the Namoi River in New South Wales, Australia.
-
E.
KNO
KNO is the IATA airport code for Kualanamu International Airport serving Medan and the surrounding region in North Sumatra, Indonesia.
- 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_69d827927c988190ad98bb0360981783 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de90283b9c8190b50d30ad58bfe085 |
completed | April 14, 2026, 7:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd551623608190ba1de09b423cc5e1 |
completed | May 8, 2026, 3:14 a.m. |
| NEDg | Description generation | batch_69fd5671340081909d87978be2a5522b |
completed | May 8, 2026, 3:20 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd57a6711881909429bba35ee867c6 |
completed | May 8, 2026, 3:25 a.m. |
Created at: April 10, 2026, 1:16 a.m.