Triple
T38665584
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Continental O-470 |
E940444
|
entity |
| Predicate | typicalCompressionRatioRange |
P12420
|
FINISHED |
| Object | 7.0:1 to 8.6:1 (depending on variant) |
—
|
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: 7.0:1 to 8.6:1 (depending on variant) | Statement: [Continental O-470, typicalCompressionRatioRange, 7.0:1 to 8.6:1 (depending on variant)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalCompressionRatioRange Context triple: [Continental O-470, typicalCompressionRatioRange, 7.0:1 to 8.6:1 (depending on variant)]
-
A.
compressionRatio
chosen
Indicates the proportional reduction in size or volume achieved when something is compressed compared to its original size.
-
B.
compressionRatioClass
Indicates the categorical classification of how much something has been compressed relative to its original size.
-
C.
compressionLevelRange
Indicates the allowable range of compression levels that can be applied in a given context.
-
D.
compressorType
Indicates the specific kind or category of compressor associated with an entity.
-
E.
compressionType
Indicates the method or format used to compress data or content in the relationship.
- 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_69f76edfde348190bf6529d9f49ecd62 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037c9141dc819098d7fcc36e69882c |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a2026248190b894436a578d79ac |
completed | May 12, 2026, 7:06 p.m. |
Created at: May 3, 2026, 4:33 p.m.