Triple
T23619135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kurzweil K2500 |
E583263
|
entity |
| Predicate | supportsSampling |
P15794
|
FINISHED |
| Object | optional sampling board |
—
|
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: optional sampling board | Statement: [Kurzweil K2500, supportsSampling, optional sampling board]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsSampling Context triple: [Kurzweil K2500, supportsSampling, optional sampling board]
-
A.
hasSampling
Indicates that one entity performs, involves, or is associated with the act or process of sampling in relation to another entity.
-
B.
usesSamplingOf
Indicates that one entity employs or relies on a sample or subset derived from another entity for its operation, analysis, or processing.
-
C.
supportsUse
chosen
Indicates that one entity enables, allows, or is compatible with the use or operation of another entity.
-
D.
samplingType
Indicates the method or strategy used to select samples from a larger set or population.
-
E.
usesSamplingOrInterpolation
Indicates that one entity applies sampling or interpolation techniques to obtain or approximate values from another entity or dataset.
- 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_69e248fbcd9081908ba08913f9d30826 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b17780a88190b6f0d6d551133454 |
completed | April 29, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69f118d0e0588190a86527a7747c5427 |
completed | April 28, 2026, 8:30 p.m. |
Created at: April 17, 2026, 6:45 p.m.