Triple
T19921576
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DJI Avata |
E478807
|
entity |
| Predicate | cameraMaxFrameRate2_7K |
P68881
|
FINISHED |
| Object | 100 fps |
—
|
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: 100 fps | Statement: [DJI Avata, cameraMaxFrameRate2_7K, 100 fps]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cameraMaxFrameRate2_7K Context triple: [DJI Avata, cameraMaxFrameRate2_7K, 100 fps]
-
A.
propertyType_maxFramerate
chosen
Indicates the maximum frame rate value that the property can support or is configured to allow.
-
B.
maximumShutterSpeed
Indicates the highest shutter speed value that can be set or achieved in a given photographic or imaging context.
-
C.
hasCameraResolution
Indicates that an entity is associated with a specific camera resolution value or specification.
-
D.
hasMaxMacroblocksPerSecond
Indicates the maximum number of macroblocks that can be processed or handled per second in a given context.
-
E.
supportsFrameRates
Indicates that one entity is capable of operating with, handling, or being compatible with the specified frame rates 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_69d8e521855c8190b41871700afc8d6a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e659c6919c8190a96106532580b6b6 |
completed | April 20, 2026, 4:52 p.m. |
| PD | Predicate disambiguation | batch_69e537f070b481908958e0e5911dcdc1 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:53 p.m.