Triple
T24813337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | JPEG 2000 |
E620848
|
entity |
| Predicate | supportsCompressionType |
P27672
|
FINISHED |
| Object | lossless 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: lossless compression | Statement: [JPEG 2000, supportsCompressionType, lossless compression]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsCompressionType Context triple: [JPEG 2000, supportsCompressionType, lossless compression]
-
A.
supportsCompressedFiles
Indicates that one entity is capable of handling, reading, or working with files that are stored in a compressed format.
-
B.
compressionType
chosen
Indicates the method or format used to compress data or content in the relationship.
-
C.
hasCompressor
Indicates that one entity is equipped with, contains, or uses a compressor associated with it.
-
D.
supportsType
Indicates that one entity is capable of handling, accepting, or being compatible with a specified type.
-
E.
compressorType
Indicates the specific kind or category of compressor associated with an entity.
- 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_69e2fabfd4648190bd0e5c7f4dbb6cab |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f606c79ad081908369605f72e65ca6 |
completed | May 2, 2026, 2:14 p.m. |
| PD | Predicate disambiguation | batch_69f602ce79ec8190b8336c2b9de18ac7 |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 18, 2026, 4:56 a.m.