Triple
T14335787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Corsair |
E355462
|
entity |
| Predicate | softwarePurpose |
P100214
|
FINISHED |
| Object | RGB lighting control |
—
|
LITERAL 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: RGB lighting control | Statement: [Corsair, softwarePurpose, RGB lighting control]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: softwarePurpose Context triple: [Corsair, softwarePurpose, RGB lighting control]
-
A.
servicePurpose
Indicates that one entity serves as the purpose, goal, or intended function for which another entity (typically a service) exists or is provided.
-
B.
softwareFor
chosen
Indicates that one entity is designed, intended, or used to operate on, support, or be compatible with another entity as software.
-
C.
programUse
Indicates that one entity uses, employs, or makes use of a particular program or software application.
-
D.
operationalPurpose
Indicates the function, role, or intended use that an entity is designed or configured to perform in an operational context.
-
E.
technologyUsedFor
Indicates that a particular technology is employed or applied to accomplish, support, or enable a specific purpose, task, or function.
- F. None of above.
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_69d8278fa2108190bc0d0e7939c1eb03 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8c20d2148190bb534bef338e871d |
completed | April 14, 2026, 6:49 p.m. |
| PD | Predicate disambiguation | batch_69de2a9958e881909d03ac03f135163e |
completed | April 14, 2026, 11:52 a.m. |
Created at: April 10, 2026, 1:14 a.m.