Triple
T26077034
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Z-Wave Alliance |
E657713
|
entity |
| Predicate | promotesUseCase |
P1258
|
FINISHED |
| Object | 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: lighting control | Statement: [Z-Wave Alliance, promotesUseCase, lighting control]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: promotesUseCase Context triple: [Z-Wave Alliance, promotesUseCase, lighting control]
-
A.
promotesUseIn
Indicates that one entity actively encourages, supports, or increases the adoption or application of another entity within a particular context or setting.
-
B.
exportUse
Indicates that something is used, intended, or suitable for export from one place or market to another.
-
C.
promotes
chosen
Indicates that one entity actively supports, advances, or encourages the growth, adoption, or success of another entity or outcome.
-
D.
hasUseCase
Indicates that one entity is employed, applied, or utilized as a solution or method to address a particular need, problem, or scenario associated with another entity.
-
E.
potentialUse
Indicates that one entity could be used for, or is suitable for, a particular function, purpose, or application involving another entity.
- 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_69ee5bbf0d208190801ee95d4f07fb16 |
completed | April 26, 2026, 6:38 p.m. |
| NER | Named-entity recognition | batch_69f661b58ac48190907b6c6e9ccc2c59 |
completed | May 2, 2026, 8:42 p.m. |
| PD | Predicate disambiguation | batch_69f660eea4648190b0d5e24293607813 |
completed | May 2, 2026, 8:39 p.m. |
Created at: April 26, 2026, 7:35 p.m.