Triple
T18564518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UTF-16 |
E453728
|
entity |
| Predicate | supportsCodePointRange |
P70659
|
FINISHED |
| Object | U+0000 to U+10FFFF |
—
|
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: U+0000 to U+10FFFF | Statement: [UTF-16, supportsCodePointRange, U+0000 to U+10FFFF]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: supportsCodePointRange Context triple: [UTF-16, supportsCodePointRange, U+0000 to U+10FFFF]
-
A.
usesCodePoints
chosen
Indicates that one entity represents, encodes, or operates using the specific set of Unicode code points defined by another entity.
-
B.
usesCodeUnitRange
Indicates that one entity operates on or is defined in terms of a specific range of code units (e.g., character or byte positions) within another entity.
-
C.
hasUnicodeCodePoint
Indicates that a character or symbol is associated with a specific numeric Unicode code point value.
-
D.
hasControlCharacterRange
Indicates that there exists a specified range of control characters associated with or applicable to an entity.
-
E.
definesCodepoint
Indicates that one entity specifies or assigns the particular codepoint value used to represent another entity in an encoding system.
- 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_69d8d38974308190a9174430ef256b73 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53afd8114819093b57d86f8213311 |
completed | April 19, 2026, 8:28 p.m. |
| PD | Predicate disambiguation | batch_69e478c16e0c8190b03966aa23c395a6 |
completed | April 19, 2026, 6:40 a.m. |
Created at: April 10, 2026, 11:42 a.m.