Triple
T17561936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DAX |
E427711
|
entity |
| Predicate | scalingModel |
P58733
|
FINISHED |
| Object | horizontal scaling by adding nodes |
—
|
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: horizontal scaling by adding nodes | Statement: [DAX, scalingModel, horizontal scaling by adding nodes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scalingModel Context triple: [DAX, scalingModel, horizontal scaling by adding nodes]
-
A.
scaleModelOf
Indicates that one entity is a scaled representation (larger or smaller but proportionally accurate) of another entity.
-
B.
scalingProperty
chosen
Indicates how a quantity or behavior changes in proportion to changes in another variable, typically under resizing or rescaling conditions.
-
C.
scaleDefinition
Indicates that an entity specifies the parameters, structure, or measurement system used to define a particular scale.
-
D.
associatedScale
Indicates that one entity is linked or connected to a particular scale used to measure, classify, or evaluate it.
-
E.
scaleProperty
Indicates that one entity defines or modifies the scale, magnitude, or proportional sizing used to interpret or represent a property of another entity.
- 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_69d889e0385081908a04b66f4dd4bd0d |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e456274c888190ac80402e391674dd |
completed | April 19, 2026, 4:12 a.m. |
| PD | Predicate disambiguation | batch_69e3b4fd7d048190b54ee4c6155612a5 |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:50 a.m.