Triple
T12516261
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | gzip |
E299197
|
entity |
| Predicate | defaultCompressionLevel |
P105399
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [gzip, defaultCompressionLevel, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: defaultCompressionLevel Context triple: [gzip, defaultCompressionLevel, 6]
-
A.
compressionType
Indicates the method or format used to compress data or content in the relationship.
-
B.
compressionGoal
Indicates the target level or outcome of data size reduction that a compression process aims to achieve.
-
C.
compressionRatio
Indicates the proportional reduction in size or volume achieved when something is compressed compared to its original size.
-
D.
headerCompressionAlgorithm
Indicates the algorithm used to compress the header portion of a data structure or message.
-
E.
optimizationLevel
Indicates the degree or intensity to which a process, system, or solution has been refined to improve its performance or efficiency.
- 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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d954b867dc8190af8a70f797e4d133 |
completed | April 10, 2026, 7:51 p.m. |
| PD | Predicate disambiguation | batch_69d954096af88190b6be81b008c82139 |
completed | April 10, 2026, 7:48 p.m. |
| PDg | Predicate description generation | batch_69d954b715fc819091fa84430be46273 |
completed | April 10, 2026, 7:51 p.m. |
Created at: April 8, 2026, 9:57 p.m.