Triple
T27666634
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | WAV |
E697244
|
entity |
| Predicate | typicalEncoding |
P201340
|
FINISHED |
| Object | uncompressed PCM audio |
—
|
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: uncompressed PCM audio | Statement: [WAV, typicalEncoding, uncompressed PCM audio]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalEncoding Context triple: [WAV, typicalEncoding, uncompressed PCM audio]
-
A.
localEncoding
Indicates that an entity is represented or stored using a specific encoding scheme that is defined or applied locally within a particular context or system.
-
B.
encodingBasisFor
Indicates that one encoding scheme serves as the foundational or reference basis for defining or interpreting another encoding.
-
C.
encodingIs
Indicates that one entity serves as the specific encoding or coded representation of another entity.
-
D.
encodingAbstraction
Indicates an abstraction relationship where one representation or model encodes, summarizes, or symbolically captures the structure or information content of another.
-
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_69ef590b85a4819083ec7c12bd3c9c10 |
completed | April 27, 2026, 12:39 p.m. |
| NER | Named-entity recognition | batch_69ffecdcbac4819093b725a7dbe0e61b |
completed | May 10, 2026, 2:26 a.m. |
| PD | Predicate disambiguation | batch_69ffec3633288190adbbd84e277708dc |
completed | May 10, 2026, 2:23 a.m. |
| PDg | Predicate description generation | batch_69ffecdbe62081909f901e7d4db69d60 |
completed | May 10, 2026, 2:26 a.m. |
Created at: April 27, 2026, 2:38 p.m.