Triple
T816190
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | MicroPython |
E17655
|
entity |
| Predicate | typicalFlashFootprint |
P19963
|
FINISHED |
| Object | hundreds of kilobytes |
—
|
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: hundreds of kilobytes | Statement: [MicroPython, typicalFlashFootprint, hundreds of kilobytes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalFlashFootprint Context triple: [MicroPython, typicalFlashFootprint, hundreds of kilobytes]
-
A.
floppyDriveCapacity
Indicates the storage capacity associated with a floppy drive.
-
B.
typicalPictureFormat
Indicates the standard or most commonly used picture format associated with an entity (such as a device, medium, or context).
-
C.
typicalWidth
Indicates the usual or characteristic width associated with an entity, as opposed to an exact or measured width in a specific instance.
-
D.
hasPhysicalFootprint
Indicates that one entity occupies or affects a specific physical area or space in the real world.
-
E.
typicalLength
Indicates the usual or characteristic length associated with an entity or phenomenon.
- 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_69a4937bcaac8190a322524ac6f45a5a |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4ab5157b08190b6c8f2fd455f261e |
completed | March 1, 2026, 9:10 p.m. |
| PD | Predicate disambiguation | batch_69a4aa756920819080ae82948974c876 |
completed | March 1, 2026, 9:07 p.m. |
| PDg | Predicate description generation | batch_69a4ab4781c88190ae36906251347cdc |
completed | March 1, 2026, 9:10 p.m. |
Created at: March 1, 2026, 7:38 p.m.