Triple
T12515352
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Intel HEX |
E299178
|
entity |
| Predicate | lineByteCountRange |
P54172
|
FINISHED |
| Object | 1–255 data bytes per record |
—
|
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: 1–255 data bytes per record | Statement: [Intel HEX, lineByteCountRange, 1–255 data bytes per record]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: lineByteCountRange Context triple: [Intel HEX, lineByteCountRange, 1–255 data bytes per record]
-
A.
codeSpaceRange
Indicates the range of code points or values that define the valid span or interval within a given code space.
-
B.
blockNumberOfCodePoints
Indicates the number of code points contained within a given block.
-
C.
minBytesPerCodePoint
Indicates the minimum number of bytes required to represent a single code point in the given encoding or data representation.
-
D.
rangeOf
Indicates that one entity specifies the set of possible values (range) that another entity’s outputs or properties can take.
-
E.
hasLengthRange
chosen
Indicates that an entity’s length falls within a specified minimum-to-maximum range.
- 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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d954b867dc8190af8a70f797e4d133 |
completed | April 10, 2026, 7:51 p.m. |
| PD | Predicate disambiguation | batch_69d954096af88190b6be81b008c82139 |
completed | April 10, 2026, 7:48 p.m. |
Created at: April 8, 2026, 9:57 p.m.