Triple
T16852915
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hisense (selected models) |
E409717
|
entity |
| Predicate | imageQualityAttribute |
P52703
|
FINISHED |
| Object | high dynamic range potential |
—
|
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: high dynamic range potential | Statement: [Hisense (selected models), imageQualityAttribute, high dynamic range potential]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: imageQualityAttribute Context triple: [Hisense (selected models), imageQualityAttribute, high dynamic range potential]
-
A.
imageQuality
chosen
Indicates the assessed level or degree of visual clarity, detail, and overall fidelity of an image.
-
B.
videoQuality
Indicates the level or standard of clarity, resolution, and overall visual fidelity associated with a given video.
-
C.
storageQuality
Indicates the degree or standard of how well something is stored, such as its preservation, safety, or suitability for use.
-
D.
hasPerceptualQuality
Indicates that something possesses a particular sensory or perceptual characteristic, such as a color, sound, texture, taste, or smell.
-
E.
sensorResolution
Indicates the level of detail or precision with which a sensor can measure or distinguish changes in the observed quantity or environment.
- 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_69d88395e6c88190b22730f335107c14 |
completed | April 10, 2026, 4:59 a.m. |
| NER | Named-entity recognition | batch_69e3b37abadc81909d02d329403497d6 |
completed | April 18, 2026, 4:38 p.m. |
| PD | Predicate disambiguation | batch_69e32b8cbb048190878a259cc5be960e |
completed | April 18, 2026, 6:58 a.m. |
Created at: April 10, 2026, 5:24 a.m.