Triple
T634370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NTSC color television standard |
E15990
|
entity |
| Predicate | originalFrameRate |
P17346
|
FINISHED |
| Object | 30 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: 30 frames per second | Statement: [NTSC color television standard, originalFrameRate, 30 frames per second]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: originalFrameRate Context triple: [NTSC color television standard, originalFrameRate, 30 frames per second]
-
A.
originalLineSpeed
Indicates the speed at which something initially moves or operates before any changes or adjustments are made.
-
B.
timeScaleType
Indicates the type or category of temporal scaling applied to an event, process, or measurement (e.g., real-time, accelerated, aggregated).
-
C.
originalHeight
Indicates the initial or starting height of an entity before any change, adjustment, or transformation occurs.
-
D.
frameType
Indicates the specific structural or categorical kind of frame associated with an entity or relation.
-
E.
clockSpeed
Indicates the operating frequency at which a clock-driven component (such as a processor) performs its cycles or operations over time.
- F. None of above. chosen
Provenance (4 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_69a4935c131c8190a5378c6bf101e8cc |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49ee4ee8481908ad45405e3f3835c |
completed | March 1, 2026, 8:17 p.m. |
| PD | Predicate disambiguation | batch_69a49d0483908190a5ec42a7403c258e |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49defe58c8190bd39ef47c9f660a7 |
completed | March 1, 2026, 8:13 p.m. |
Created at: March 1, 2026, 7:35 p.m.