Triple
T9175789
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | DTS-HD Master Audio |
E220195
|
entity |
| Predicate | supportsLossyCore |
P203
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [DTS-HD Master Audio, supportsLossyCore, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsLossyCore Context triple: [DTS-HD Master Audio, supportsLossyCore, true]
-
A.
isLossless
Indicates that a transformation, compression, or process preserves all original information without any loss of data.
-
B.
hasCore
Indicates that one entity possesses, contains, or is built around a central or most essential component represented by another entity.
-
C.
supportsRobustLowBitrateModes
Indicates that something is capable of operating effectively and reliably at low data bitrates, maintaining acceptable performance or quality under such constrained conditions.
-
D.
supportsFeature
chosen
Indicates that one entity provides, enables, or is compatible with a particular feature or capability of another.
-
E.
hasSecondaryCore
Indicates that an entity possesses an additional, subordinate core component alongside its primary core.
- 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_69ca83e589948190ac9907819db11ddf |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccbfa496548190a096969eebf732f3 |
completed | April 1, 2026, 6:48 a.m. |
| PD | Predicate disambiguation | batch_69cc660761d88190ab6134b43b376964 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:23 p.m.