Triple
T8152039
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | xVelocity in-memory analytics engine |
E190354
|
entity |
| Predicate | compressionTechnique |
P27672
|
FINISHED |
| Object | dictionary encoding |
—
|
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: dictionary encoding | Statement: [xVelocity in-memory analytics engine, compressionTechnique, dictionary encoding]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: compressionTechnique Context triple: [xVelocity in-memory analytics engine, compressionTechnique, dictionary encoding]
-
A.
compressionType
chosen
Indicates the method or format used to compress data or content in the relationship.
-
B.
compressionRatio
Indicates the proportional reduction in size or volume achieved when something is compressed compared to its original size.
-
C.
compressionDomain
Indicates a relationship where one entity serves as the domain or context within which another entity’s compression or compression-related process is defined or applied.
-
D.
compressorType
Indicates the specific kind or category of compressor associated with an entity.
-
E.
compressionScope
Indicates the extent or range within which compression is applied to data or content.
- 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_69ca82be7ba8819087de0147e9292c83 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4483799c81908e73f9a87ed99185 |
completed | March 31, 2026, 3:50 a.m. |
| PD | Predicate disambiguation | batch_69cb36a0847c8190af9038aef78319b3 |
completed | March 31, 2026, 2:51 a.m. |
Created at: March 30, 2026, 5:37 p.m.