Triple
T4279042
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MySQL HeatWave |
E97107
|
entity |
| Predicate | processingModel |
P5328
|
FINISHED |
| Object | in-memory |
—
|
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: in-memory | Statement: [MySQL HeatWave, processingModel, in-memory]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: processingModel Context triple: [MySQL HeatWave, processingModel, in-memory]
-
A.
processingUse
Indicates that one entity uses or applies another entity as part of a processing or transformation activity.
-
B.
performanceModel
Indicates a relationship where one entity serves as a performance model that represents, predicts, or characterizes the performance behavior of another entity.
-
C.
executionModel
chosen
Indicates how a process, task, or operation is carried out or implemented, specifying the underlying method, strategy, or mechanism of its execution.
-
D.
model
Indicates that one entity serves as a representation, example, or simulation of another entity or concept.
-
E.
trainingModel
Indicates that an entity is engaged in the process of teaching, adjusting, or optimizing a model using data or experience.
- 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_69b34544be3c819084d1ab82d29f90c5 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b350201ac88190b9d8980da5f0d03d |
completed | March 12, 2026, 11:45 p.m. |
| PD | Predicate disambiguation | batch_69b347faa45481908c19c29fb906dc92 |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:07 p.m.