Triple
T4575122
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Basic Multilingual Plane |
E123124
|
entity |
| Predicate | codePointCount |
P58044
|
FINISHED |
| Object | 65536 |
—
|
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: 65536 | Statement: [Basic Multilingual Plane, codePointCount, 65536]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: codePointCount Context triple: [Basic Multilingual Plane, codePointCount, 65536]
-
A.
maximumCodePoints
Indicates the maximum number of Unicode code points that are allowed or supported in a given context or value.
-
B.
hasUnicodeCodePoint
Indicates that a character or symbol is associated with a specific numeric Unicode code point value.
-
C.
unicodeCodePoint
Indicates that a character or symbol is associated with a specific Unicode code point value in the Unicode standard.
-
D.
UnicodeCodePointFinal
Indicates that one entity is the final (last) Unicode code point in a specified sequence or representation associated with another entity.
-
E.
DELCodePoint
Indicates a relationship where a specific code point corresponds to or is designated as the delete (DEL) control character in a character encoding system.
- 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_69bd46466c7081909d07f36be2d08804 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd58c9f0bc81908d87f01ab067818a |
completed | March 20, 2026, 2:25 p.m. |
| PD | Predicate disambiguation | batch_69bd5228b70c8190ac48705e35a710c1 |
completed | March 20, 2026, 1:56 p.m. |
| PDg | Predicate description generation | batch_69bd56b4a9508190acdb888eef18f1ee |
completed | March 20, 2026, 2:16 p.m. |
Created at: March 20, 2026, 1:10 p.m.