Triple
T6034219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RTCRtpEncodingParameters |
E134377
|
entity |
| Predicate | propertyType_scaleResolutionDownBy |
P68882
|
FINISHED |
| Object | double |
—
|
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: double | Statement: [RTCRtpEncodingParameters, propertyType_scaleResolutionDownBy, double]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: propertyType_scaleResolutionDownBy Context triple: [RTCRtpEncodingParameters, propertyType_scaleResolutionDownBy, double]
-
A.
pixelScale
Indicates the ratio or conversion factor between pixel units and real-world or coordinate-space units in a representation or image.
-
B.
areaScale
Indicates a proportional relationship where one area value is a scaled (enlarged or reduced) version of another by a specific factor.
-
C.
scalingProperty
Indicates how a quantity or behavior changes in proportion to changes in another variable, typically under resizing or rescaling conditions.
-
D.
typicalResolution
Indicates the usual or standard level of detail or clarity at which something (such as an image, display, or representation) is normally rendered or presented.
-
E.
hasSpatialResolution
Indicates that something is characterized by a specific level of spatial detail or granularity at which it can represent or distinguish features in space.
- F. None of above. chosen
Provenance (4 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_69c00875db5c819099dd5bb833ec43c2 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c056b220608190b156be95632cf3b3 |
completed | March 22, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69c049e9a68c81909da0cfe4779ce9b5 |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04e8c5bfc8190b986a7071d1b23e3 |
completed | March 22, 2026, 8:18 p.m. |
Created at: March 22, 2026, 4:08 p.m.