Triple
T21169062
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Woz Monitor |
E521644
|
entity |
| Predicate | codeSize |
P66348
|
FINISHED |
| Object | approximately 256 bytes |
—
|
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: approximately 256 bytes | Statement: [Woz Monitor, codeSize, approximately 256 bytes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: codeSize Context triple: [Woz Monitor, codeSize, approximately 256 bytes]
-
A.
scriptCodeLength
Indicates the length or number of characters in a given script or code sequence.
-
B.
codeDensity
Indicates the proportion of code elements (such as instructions, statements, or functionality) relative to a given size or resource measure (e.g., lines, bytes, or area).
-
C.
instructionSetSize
Indicates the size or number of instructions defined in an instruction set.
-
D.
instructionLength
Indicates the duration or amount of time required to carry out a given instruction or operation.
-
E.
hasCodeSpaceSize
chosen
Indicates the size or capacity of the code space associated with an entity, such as the range or number of distinct codes it can represent.
- 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_69e0b50e30748190b186824a206d39b9 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e72711be9481909f16107b71d3500a |
completed | April 21, 2026, 7:28 a.m. |
| PD | Predicate disambiguation | batch_69e5f6027c248190a170a36612bd337e |
completed | April 20, 2026, 9:46 a.m. |
Created at: April 16, 2026, 3 p.m.