Triple
T14576733
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nokia N73 |
E342071
|
entity |
| Predicate | videoRecordingFrameRate |
P68881
|
FINISHED |
| Object | 15 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: 15 fps | Statement: [Nokia N73, videoRecordingFrameRate, 15 fps]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: videoRecordingFrameRate Context triple: [Nokia N73, videoRecordingFrameRate, 15 fps]
-
A.
commonFrameRate
Indicates that two or more media items share the same frame rate.
-
B.
propertyType_maxFramerate
chosen
Indicates the maximum frame rate value that the property can support or is configured to allow.
-
C.
videoEncoding
Indicates that one entity is used to encode, compress, or transform video data into a particular digital format or representation for another entity.
-
D.
videoQuality
Indicates the level or standard of clarity, resolution, and overall visual fidelity associated with a given video.
-
E.
originalFrameRate
Indicates the frame rate at which the original media content was captured or encoded before any conversion or processing.
- 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_69d822dcc6248190bed689984bceb0e2 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb3f5ec448190b2ef887fdf7b633e |
completed | April 14, 2026, 9:39 p.m. |
| PD | Predicate disambiguation | batch_69de656a953481909a4645b004c40de7 |
completed | April 14, 2026, 4:03 p.m. |
Created at: April 10, 2026, 1:24 a.m.