Triple
T1774667
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Commodore Amiga 1000 |
E38950
|
entity |
| Predicate | audioSampleRates |
P31523
|
FINISHED |
| Object | up to ~28 kHz per channel |
—
|
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: up to ~28 kHz per channel | Statement: [Commodore Amiga 1000, audioSampleRates, up to ~28 kHz per channel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: audioSampleRates Context triple: [Commodore Amiga 1000, audioSampleRates, up to ~28 kHz per channel]
-
A.
soundRecordingSpeed
Indicates the recording speed at which an audio recording was captured or is intended to be played back.
-
B.
audioChannels
Indicates the number or configuration of distinct audio signal paths (such as mono, stereo, or surround) used in a recording, transmission, or playback.
-
C.
supportsAudioQuality
Indicates that one entity provides or is compatible with a specified level or type of audio quality for another entity or context.
-
D.
soundReproductionMethod
Indicates the method or technique used to reproduce or play back sound.
-
E.
dataRate
Indicates the rate at which data is transmitted, processed, or transferred between entities over a given time interval.
- 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_69a8862e61708190af97b9838cc3f5de |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69ab17e368048190b7b73d156400f772 |
completed | March 6, 2026, 6:07 p.m. |
| PD | Predicate disambiguation | batch_69aa61cd4c1c8190a8dff391f5642bfe |
completed | March 6, 2026, 5:10 a.m. |
| PDg | Predicate description generation | batch_69ab17d0a644819087e6ce39d6c60da5 |
completed | March 6, 2026, 6:07 p.m. |
Created at: March 4, 2026, 7:31 p.m.