Triple
T23257166
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kikakui script |
E581903
|
entity |
| Predicate | UnicodeVersionEncoded |
P27273
|
FINISHED |
| Object | Unicode 7.0 |
—
|
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: Unicode 7.0 | Statement: [Kikakui script, UnicodeVersionEncoded, Unicode 7.0]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: UnicodeVersionEncoded Context triple: [Kikakui script, UnicodeVersionEncoded, Unicode 7.0]
-
A.
UnicodeStandardVersionIntroduced
Indicates the specific version of the Unicode Standard in which a given character, feature, or property was first introduced.
-
B.
encodedInUnicodeSince
chosen
Indicates that a given character or symbol has been included and assigned a code point in the Unicode standard starting from a specific version or time.
-
C.
UnicodePlane
Indicates that a Unicode code point belongs to a specific Unicode plane (a contiguous range of code points grouped by plane number).
-
D.
unicodeCodePoint
Indicates that a character or symbol is associated with a specific Unicode code point value in the Unicode standard.
-
E.
UnicodeCodePointStandard
Indicates that a Unicode code point conforms to, or is defined within, a particular Unicode standard or version.
- 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_69e246079f58819085eaa9c260906880 |
completed | April 17, 2026, 2:39 p.m. |
| NER | Named-entity recognition | batch_69f194c5f5bc8190ac8776f7f7430209 |
completed | April 29, 2026, 5:19 a.m. |
| PD | Predicate disambiguation | batch_69effce4d704819092826931d430e8c4 |
completed | April 28, 2026, 12:18 a.m. |
Created at: April 17, 2026, 4:11 p.m.