Triple
T6442147
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | RFC 3629 |
E138249
|
entity |
| Predicate | definesCodeUnitSequenceLength |
P70662
|
FINISHED |
| Object | 1 to 4 octets |
—
|
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 to 4 octets | Statement: [RFC 3629, definesCodeUnitSequenceLength, 1 to 4 octets]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: definesCodeUnitSequenceLength Context triple: [RFC 3629, definesCodeUnitSequenceLength, 1 to 4 octets]
-
A.
blockNumberOfCodePoints
Indicates the number of code points contained within a given block.
-
B.
codingUnit
Indicates a relationship where an entity functions as or is associated with a specific unit of code or coding structure.
-
C.
maximumCodePoints
Indicates the maximum number of Unicode code points that are allowed or supported in a given context or value.
-
D.
repeatUnitLength
Indicates the length or size of a unit that is repeated within a larger pattern, sequence, or structure.
-
E.
codePointCount
Indicates the number of Unicode code points contained within a specified range of a character sequence.
- 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_69c008aa61ac8190bc96715ed79fe2d8 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c06989dfb88190b25ff8b2c53f3ced |
completed | March 22, 2026, 10:13 p.m. |
| PD | Predicate disambiguation | batch_69c060faaf248190bbdc8ff909c8777a |
completed | March 22, 2026, 9:36 p.m. |
| PDg | Predicate description generation | batch_69c0623e3cd48190929b0e3cba013909 |
completed | March 22, 2026, 9:42 p.m. |
Created at: March 22, 2026, 4:46 p.m.