Triple
T29863904
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | mod_brotli |
E758395
|
entity |
| Predicate | compressionLevelRange |
P167682
|
FINISHED |
| Object | 0-11 |
—
|
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: 0-11 | Statement: [mod_brotli, compressionLevelRange, 0-11]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: compressionLevelRange Context triple: [mod_brotli, compressionLevelRange, 0-11]
-
A.
compressionType
Indicates the method or format used to compress data or content in the relationship.
-
B.
compressionGranularity
Indicates the level of detail or size of units at which data or content is compressed within a system or process.
-
C.
compressionMode
Indicates the specific method or setting used to compress data or content in a given context.
-
D.
defaultCompressionLevel
Indicates the standard or preconfigured degree of compression applied when no specific compression level is explicitly set.
-
E.
compressionRatio
Indicates the proportional reduction in size or volume achieved when something is compressed compared to its original size.
- 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_69f2245b4dec8190b85f664d918a00a5 |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f67687612c8190b4781cfe3898bf7f |
completed | May 2, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69f66ac32b60819092290b2de35988d3 |
completed | May 2, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69f66bd123108190b451eb6e23842adb |
completed | May 2, 2026, 9:25 p.m. |
Created at: April 29, 2026, 5:50 p.m.