Triple
T3986811
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dolby TrueHD |
E86890
|
entity |
| Predicate | compressionDomain |
P53676
|
FINISHED |
| Object | frequency domain |
—
|
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: frequency domain | Statement: [Dolby TrueHD, compressionDomain, frequency domain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: compressionDomain Context triple: [Dolby TrueHD, compressionDomain, frequency domain]
-
A.
compressionScope
Indicates the extent or range within which compression is applied to data or content.
-
B.
compressionType
Indicates the method or format used to compress data or content in the relationship.
-
C.
compressionRatio
Indicates the proportional reduction in size or volume achieved when something is compressed compared to its original size.
-
D.
compressorType
Indicates the specific kind or category of compressor associated with an entity.
-
E.
encodes
Indicates that one entity contains or represents the information, instructions, or structure of another in a coded or symbolic 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_69aed93fd9d4819085d3b2137d2346cb |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefb81040481909b22e4c445ecae0f |
completed | March 9, 2026, 4:55 p.m. |
| PD | Predicate disambiguation | batch_69aef8f692008190bf4d637ffc3d3eaa |
completed | March 9, 2026, 4:44 p.m. |
| PDg | Predicate description generation | batch_69aefb7f92348190ae35f1d75b0b5d4f |
completed | March 9, 2026, 4:55 p.m. |
Created at: March 9, 2026, 3:33 p.m.