Triple
T29392049
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SPI |
E745388
|
entity |
| Predicate | typicalDataFrameSize |
P203615
|
FINISHED |
| Object | 8 bits |
—
|
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: 8 bits | Statement: [SPI, typicalDataFrameSize, 8 bits]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalDataFrameSize Context triple: [SPI, typicalDataFrameSize, 8 bits]
-
A.
typicalFileSizeCharacteristic
Indicates the usual or characteristic file size associated with an entity, such as a resource, dataset, or document.
-
B.
typicalCellSize
Indicates the usual or characteristic physical size associated with a given cell.
-
C.
typicalDimension
Indicates that one entity represents a standard or characteristic measurement (such as size, length, or capacity) typically associated with another entity.
-
D.
typicalKeyCount
Indicates the usual or standard number of keys associated with an entity in this context.
-
E.
typicalNumberOfComponents
Indicates the usual or standard count of distinct components that an entity is expected to have.
- 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_69f0a79dfabc81908755382ee47791e2 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_6a01b3af7b908190b4675c85d32d106c |
completed | May 11, 2026, 10:47 a.m. |
| PD | Predicate disambiguation | batch_6a01b35813c081908e484b2b9ca5dd05 |
completed | May 11, 2026, 10:45 a.m. |
| PDg | Predicate description generation | batch_6a01b3ae7f948190b93fbe0add0dbcec |
completed | May 11, 2026, 10:47 a.m. |
Created at: April 28, 2026, 2:43 p.m.