Triple
T30383882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sony WH-XB700 |
E772896
|
entity |
| Predicate | noiseCancellation |
P44489
|
FINISHED |
| Object | no active noise cancelling |
—
|
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: no active noise cancelling | Statement: [Sony WH-XB700, noiseCancellation, no active noise cancelling]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: noiseCancellation Context triple: [Sony WH-XB700, noiseCancellation, no active noise cancelling]
-
A.
noiseReductionFeature
chosen
Indicates that an entity includes or supports a capability to reduce or minimize unwanted noise.
-
B.
noiseReductionType
Indicates the specific method or technique used to reduce or minimize noise in a given context.
-
C.
usesCrosstalkCancellation
Indicates that one entity applies crosstalk cancellation techniques to reduce or eliminate interference between signals associated with another entity.
-
D.
noiseLevel
Indicates the intensity or amount of sound present in a given environment or from a specific source.
-
E.
usesEchoCancellation
Indicates that an entity employs echo cancellation techniques to reduce or eliminate echo in audio communication.
- 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_69f2248e3444819081b05712dc6873de |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68f670b608190a0b6ab60d722b4e0 |
completed | May 2, 2026, 11:57 p.m. |
| PD | Predicate disambiguation | batch_69f68b7b03488190b1db5fde4c7dd6e5 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 29, 2026, 8:01 p.m.