Triple
T32013542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | KL10 |
E817471
|
entity |
| Predicate | bitAddressable |
P173114
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [KL10, bitAddressable, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bitAddressable Context triple: [KL10, bitAddressable, yes]
-
A.
bitLocation
Indicates the specific position or index of a bit within a binary sequence or data structure.
-
B.
wordAddressable
Indicates that data in a memory or storage system can be individually accessed and manipulated at the granularity of single words rather than larger blocks or bytes.
-
C.
supportsByteAddressing
Indicates that one entity provides the capability for direct access to individual bytes within its addressable memory or data space for another entity.
-
D.
bitWidth
Indicates the number of bits used to represent or encode a given value, type, or data element.
-
E.
bitSlice
Indicates taking a contiguous subset of bits from a larger bit sequence, defined by specified start and end positions.
- 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_69f348f9e5d081908cc3f57c4942af52 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b43932788190bff57095264a917d |
completed | May 3, 2026, 2:34 a.m. |
| PD | Predicate disambiguation | batch_69f6b151ad008190836c1bcdec503ce2 |
completed | May 3, 2026, 2:22 a.m. |
| PDg | Predicate description generation | batch_69f6b21da77081908c5c015c4606d344 |
completed | May 3, 2026, 2:25 a.m. |
Created at: May 1, 2026, 12:15 a.m.