Triple
T1407308
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dolby Digital 5.1 |
E31722
|
entity |
| Predicate | compressionType |
P27672
|
FINISHED |
| Object | lossy audio compression |
—
|
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: lossy audio compression | Statement: [Dolby Digital 5.1, compressionType, lossy audio compression]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: compressionType Context triple: [Dolby Digital 5.1, compressionType, lossy audio compression]
-
A.
compressionRatio
Indicates the proportional reduction in size or volume achieved when something is compressed compared to its original size.
-
B.
headerCompressionAlgorithm
Indicates the algorithm used to compress the header portion of a data structure or message.
-
C.
lensCompressionFactor
Indicates the degree to which a lens alters perceived depth and distance relationships in an image compared to real-world geometry.
-
D.
rinkType
Indicates the specific kind or category of rink associated with an entity (e.g., ice rink, roller rink, practice rink).
-
E.
compilationType
Indicates the specific method or mode by which something is compiled or assembled into a final form.
- 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_69a49918e1f88190ba610f9dc8114578 |
completed | March 1, 2026, 7:52 p.m. |
| NER | Named-entity recognition | batch_69a4c3be10348190ade8a73780d2c008 |
completed | March 1, 2026, 10:54 p.m. |
| PD | Predicate disambiguation | batch_69a4bf030a388190bc82d30b9233e873 |
completed | March 1, 2026, 10:34 p.m. |
| PDg | Predicate description generation | batch_69a4c11067b48190bca6ef3ac1475c20 |
completed | March 1, 2026, 10:43 p.m. |
Created at: March 1, 2026, 7:59 p.m.