Triple
T1380958
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ISO/IEC 8859-1 |
E29335
|
entity |
| Predicate | controlCharactersRange |
P23703
|
FINISHED |
| Object | 0–31 |
—
|
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: 0–31 | Statement: [ISO/IEC 8859-1, controlCharactersRange, 0–31]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: controlCharactersRange Context triple: [ISO/IEC 8859-1, controlCharactersRange, 0–31]
-
A.
hasControlCharacterRange
chosen
Indicates that there exists a specified range of control characters associated with or applicable to an entity.
-
B.
printableCharacterRange
Indicates the range of characters that are considered printable within a given character set or encoding.
-
C.
UnicodeBlock
Indicates that a character belongs to a specific contiguous range of code points defined as a Unicode block.
-
D.
legalCharacter
Indicates that an entity possesses a status, role, or nature that is recognized and defined by law.
-
E.
basicMultilingualPlaneRange
Indicates that the referenced value or code point range lies within the Basic Multilingual Plane (BMP) of the Unicode character set.
- 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_69a498d883a48190bfdca525296ef7ee |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c31b176c8190a896183140c5c8be |
completed | March 1, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69a4befe343c81909f758440a531b5be |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:59 p.m.