Triple
T24148854
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ISO/IEC 8859-13 |
E598468
|
entity |
| Predicate | codePoints0to127 |
P70659
|
FINISHED |
| Object | identical to ASCII |
—
|
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: identical to ASCII | Statement: [ISO/IEC 8859-13, codePoints0to127, identical to ASCII]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: codePoints0to127 Context triple: [ISO/IEC 8859-13, codePoints0to127, identical to ASCII]
-
A.
unicodeCodePoint
Indicates that a character or symbol is associated with a specific Unicode code point value in the Unicode standard.
-
B.
UnicodePlane
Indicates that a Unicode code point belongs to a specific Unicode plane (a contiguous range of code points grouped by plane number).
-
C.
definesCodepoint
Indicates that one entity specifies or assigns the particular codepoint value used to represent another entity in an encoding system.
-
D.
codePointType
Indicates the classification or category assigned to a specific Unicode code point (such as letter, digit, punctuation, etc.).
-
E.
usesCodePoints
chosen
Indicates that one entity represents, encodes, or operates using the specific set of Unicode code points defined by another entity.
- 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_69e288c9e488819093dd1acd91b08b8a |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1e00d252c8190a02bec29189baad0 |
completed | April 29, 2026, 10:40 a.m. |
| PD | Predicate disambiguation | batch_69f176585f3481909beb907de252cd98 |
completed | April 29, 2026, 3:09 a.m. |
Created at: April 17, 2026, 11:30 p.m.