Triple
T28470842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | STS-1 |
E720431
|
entity |
| Predicate | hasFrameRate |
P17346
|
FINISHED |
| Object | 8000 frames per second |
—
|
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: 8000 frames per second | Statement: [STS-1, hasFrameRate, 8000 frames per second]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFrameRate Context triple: [STS-1, hasFrameRate, 8000 frames per second]
-
A.
supportsFrameRates
Indicates that one entity is capable of operating with, handling, or being compatible with the specified frame rates of another entity.
-
B.
originalFrameRate
chosen
Indicates the frame rate at which the original media content was captured or encoded before any conversion or processing.
-
C.
commonFrameRate
Indicates that two or more media items share the same frame rate.
-
D.
propertyType_maxFramerate
Indicates the maximum frame rate value that the property can support or is configured to allow.
-
E.
frameDuration
Indicates the length of time that a single frame in a sequence (such as video or animation) is displayed before advancing to the next frame.
- 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_69f01a5983f48190b7c1b8857245a4f7 |
completed | April 28, 2026, 2:24 a.m. |
| NER | Named-entity recognition | batch_69f68f670b608190a0b6ab60d722b4e0 |
completed | May 2, 2026, 11:57 p.m. |
| PD | Predicate disambiguation | batch_69f68b78f29481908cc8f390496dee97 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 28, 2026, 2:48 a.m.