Triple
T28583175
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MPEG-1 Audio Layer III |
E723429
|
entity |
| Predicate | compressionRatioTypical |
P12420
|
FINISHED |
| Object | about 1:10 compared to uncompressed PCM |
—
|
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: about 1:10 compared to uncompressed PCM | Statement: [MPEG-1 Audio Layer III, compressionRatioTypical, about 1:10 compared to uncompressed PCM]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: compressionRatioTypical Context triple: [MPEG-1 Audio Layer III, compressionRatioTypical, about 1:10 compared to uncompressed PCM]
-
A.
compressionRatio
chosen
Indicates the proportional reduction in size or volume achieved when something is compressed compared to its original size.
-
B.
compressionType
Indicates the method or format used to compress data or content in the relationship.
-
C.
compressionCharacteristic
Indicates how an entity behaves or performs when subjected to compressive forces or pressure.
-
D.
compressionMode
Indicates the specific method or setting used to compress data or content in a given context.
-
E.
compressionLoss
Indicates that some amount of information, quality, or fidelity is lost as a result of a compression process.
- 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_69f01d7f92e481909847f5f3f3174a89 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f652a492108190b885b955ce147d3c |
completed | May 2, 2026, 7:38 p.m. |
| PD | Predicate disambiguation | batch_69f651aad92c8190b874b3b5f9f64434 |
completed | May 2, 2026, 7:34 p.m. |
Created at: April 28, 2026, 4:16 a.m.