Triple
T2207292
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Opera Mini |
E50829
|
entity |
| Predicate | compressionMethod |
P27672
|
FINISHED |
| Object | server-side 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: server-side compression | Statement: [Opera Mini, compressionMethod, server-side compression]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: compressionMethod Context triple: [Opera Mini, compressionMethod, server-side compression]
-
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.
compressorType
Indicates the specific kind or category of compressor associated with an entity.
-
D.
headerCompressionAlgorithm
Indicates the algorithm used to compress the header portion of a data structure or message.
-
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_69a88b06709c8190978fb2418470d1b6 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc1baa0948190b07ffc347a4f714e |
completed | March 7, 2026, 6:12 a.m. |
| PD | Predicate disambiguation | batch_69abbda8a6dc8190aa855ce2d17194b1 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:46 p.m.