Triple
T11536187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yoko |
E273553
|
entity |
| Predicate | commonKanjiComponent |
P99564
|
FINISHED |
| Object | 陽 |
—
|
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: 陽 | Statement: [Yoko, commonKanjiComponent, 陽]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: commonKanjiComponent Context triple: [Yoko, commonKanjiComponent, 陽]
-
A.
componentKanji2
Indicates that one kanji character serves as the second component or sub-part of another kanji.
-
B.
kanji
Indicates that an entity is written in, represented by, or associated with a specific kanji character or set of kanji characters.
-
C.
usesKanjiFrom
Indicates that one writing system, word, or text incorporates or is composed of kanji characters originating from another specified source.
-
D.
typicalKanjiMeaning
Indicates that one entity is the standard or commonly accepted meaning associated with a given kanji character.
-
E.
typicalKanjiSpelling
Indicates that one written form is the standard or most commonly used kanji spelling for another expression (such as a word or phrase).
- 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_69d6aae3fbec8190a14632a5df2538b6 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8839b4bb48190b748ec4119f36c11 |
completed | April 10, 2026, 4:59 a.m. |
| PD | Predicate disambiguation | batch_69d80879fdb48190be6dacc8aa63c809 |
completed | April 9, 2026, 8:13 p.m. |
| PDg | Predicate description generation | batch_69d8279925e4819089210611c0d8e61a |
completed | April 9, 2026, 10:26 p.m. |
Created at: April 8, 2026, 9:37 p.m.