Triple
T30153713
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yuki Suzuki |
E766464
|
entity |
| Predicate | possibleKanjiMeanings |
P106549
|
FINISHED |
| Object | snow (for Yuki) |
—
|
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: snow (for Yuki) | Statement: [Yuki Suzuki, possibleKanjiMeanings, snow (for Yuki)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: possibleKanjiMeanings Context triple: [Yuki Suzuki, possibleKanjiMeanings, snow (for Yuki)]
-
A.
possibleKanjiMeaning
chosen
Indicates that a given meaning is a possible or candidate interpretation associated with a particular kanji character.
-
B.
componentKanji1Meaning
Indicates that the first kanji component of a character corresponds to a particular meaning or semantic value.
-
C.
typicalKanjiMeaning
Indicates that one entity is the standard or commonly accepted meaning associated with a given kanji character.
-
D.
hasMeaningInJapanese
Indicates that something (such as a word, phrase, or symbol) possesses a specific meaning when interpreted in the Japanese language.
-
E.
meaningDependsOnKanji
Indicates that the meaning of something (e.g., a word or expression) is determined by, or varies according to, the specific kanji characters used.
- 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_69f22479cd088190ab4c6f3fce39d1c5 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6c49627908190b3553474c7c3072b |
completed | May 3, 2026, 3:44 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f23ae081909a52801266063a3c |
completed | May 3, 2026, 3:41 a.m. |
Created at: April 29, 2026, 7:20 p.m.