Triple
T21746196
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charles Brenton Fisk |
E536793
|
entity |
| Predicate | preferredTuningAndScalingApproach |
P28297
|
FINISHED |
| Object | historically informed scaling and voicing |
—
|
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: historically informed scaling and voicing | Statement: [Charles Brenton Fisk, preferredTuningAndScalingApproach, historically informed scaling and voicing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: preferredTuningAndScalingApproach Context triple: [Charles Brenton Fisk, preferredTuningAndScalingApproach, historically informed scaling and voicing]
-
A.
tuningMethod
chosen
Indicates the method or approach used to adjust or optimize something’s parameters or performance.
-
B.
tuningType
Indicates the specific method or configuration by which something is adjusted or calibrated to achieve a desired performance or behavior.
-
C.
scalability
Indicates the capacity of a system, process, or solution to handle increasing amounts of work, users, or data by efficiently expanding its resources or performance.
-
D.
scaleOptimizedFor
Indicates that something has been adjusted or configured to operate most efficiently at a particular size, level, or magnitude.
-
E.
requiresFeatureScaling
Indicates that applying feature scaling is a necessary preprocessing step for the associated data or model.
- 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_69e0c46df5448190b4322127ffc4c690 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f01a76540c8190b91a67f4a70869fb |
completed | April 28, 2026, 2:24 a.m. |
| PD | Predicate disambiguation | batch_69e6969c16fc8190b5126c169317d85d |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:49 p.m.