Triple
T27660964
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nest Wifi |
E697119
|
entity |
| Predicate | maxRecommendedCoveragePerPoint |
P163516
|
FINISHED |
| Object | up to about 1600 square feet |
—
|
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: up to about 1600 square feet | Statement: [Nest Wifi, maxRecommendedCoveragePerPoint, up to about 1600 square feet]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maxRecommendedCoveragePerPoint Context triple: [Nest Wifi, maxRecommendedCoveragePerPoint, up to about 1600 square feet]
-
A.
maxRecommendedCoveragePerRouter
Indicates the maximum amount of coverage that is recommended to be handled by a single router.
-
B.
maximumDotsPerPlace
Indicates the upper limit on how many dots are allowed to be associated with a single place.
-
C.
corePointsMaximum
Indicates the maximum number of core points that can be assigned, accumulated, or recognized within a given system or context.
-
D.
maximumSlotsRecommended
Indicates the highest number of slots that is advised or suggested to be used in a given context.
-
E.
maximumGradient
Indicates the greatest rate of change or steepest slope that occurs within a given function, surface, or dataset.
- F. None of above. chosen
Provenance (4 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_69ef590b85a4819083ec7c12bd3c9c10 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69f6397b64f881909d811225e57aac5e |
completed | May 2, 2026, 5:50 p.m. |
| PD | Predicate disambiguation | batch_69f6370c8c7c8190a02ea82847bb6e76 |
completed | May 2, 2026, 5:40 p.m. |
| PDg | Predicate description generation | batch_69f63893cc188190883ac9321a95d2dc |
completed | May 2, 2026, 5:46 p.m. |
Created at: April 27, 2026, 2:36 p.m.