Triple
T8823799
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NVIDIA Reflex |
E209964
|
entity |
| Predicate | measurementCapability |
P55904
|
FINISHED |
| Object | system latency measurement |
—
|
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: system latency measurement | Statement: [NVIDIA Reflex, measurementCapability, system latency measurement]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: measurementCapability Context triple: [NVIDIA Reflex, measurementCapability, system latency measurement]
-
A.
measurement
Indicates a relationship where one entity quantifies or assigns a value to some property, attribute, or extent of another entity according to a defined scale or standard.
-
B.
hasMeasurement
Indicates that an entity is associated with a specific measured value, often including a unit or measurement context.
-
C.
measuredProperty
Indicates that the subject is a measurement that quantifies or assesses the specified property of an entity.
-
D.
capabilityType
chosen
Indicates the type or category of capability that an entity possesses or is associated with.
-
E.
usesMeasurementTechnique
Indicates that an entity performs, applies, or relies on a specified measurement technique to obtain quantitative or qualitative data.
- 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_69ca8364e13081909c85fe80f44fe86f |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc6030b25081909d67488b35a72e05 |
completed | April 1, 2026, midnight |
| PD | Predicate disambiguation | batch_69cc5c21e64c81908490e3b0875dc0d6 |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:46 p.m.