Triple
T8286610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Samsung Ativ S |
E193800
|
entity |
| Predicate | videoRecordingResolution |
P15682
|
FINISHED |
| Object | 1080p |
—
|
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: 1080p | Statement: [Samsung Ativ S, videoRecordingResolution, 1080p]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: videoRecordingResolution Context triple: [Samsung Ativ S, videoRecordingResolution, 1080p]
-
A.
videoQuality
chosen
Indicates the level or standard of clarity, resolution, and overall visual fidelity associated with a given video.
-
B.
videoStandard
Indicates the video format or broadcasting standard that applies to a given video or recording.
-
C.
sensorResolution
Indicates the level of detail or precision with which a sensor can measure or distinguish changes in the observed quantity or environment.
-
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.
videoEncoding
Indicates that one entity is used to encode, compress, or transform video data into a particular digital format or representation for 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_69ca82e32db481908b72f3804fa71152 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7ad3722481908076508908d18621 |
completed | March 31, 2026, 7:42 a.m. |
| PD | Predicate disambiguation | batch_69cb70ad9fc081908741f8c4a4141edf |
completed | March 31, 2026, 6:58 a.m. |
Created at: March 30, 2026, 5:52 p.m.