Corpus composition research
Kanji Pair Research
Enter one kanji to discover other characters recorded in the same JMnedict name spellings, or enter two kanji to inspect that exact co-occurrence. Every count in this research view describes the imported corpus—not population popularity in Japan.
万
Jōyō · KANJIDIC grade 2 · 3 strokes
葉ten thousand, 10,000
Jōyō · KANJIDIC grade 3 · 12 strokes
Find exact-kanji names →leaf, plane, lobe
Recorded names
Name readings containing both characters
The pair only has to occur in the same written form; the two kanji are not required to be adjacent unless counted in the adjacency statistics above.
Given name
万葉実
2 source-recorded spellings in this reading group contain both 万 and 葉Given nameMayomi
まよみ
万葉
1 source-recorded spelling in this reading group contain both 万 and 葉Given nameMaya
まや
万葉
1 source-recorded spelling in this reading group contain both 万 and 葉Given nameKazuyo
かずよ
万葉
1 source-recorded spelling in this reading group contain both 万 and 葉Given nameMitsuyo
みつよ
万葉
1 source-recorded spelling in this reading group contain both 万 and 葉Given nameMayo
まよ
万葉
1 source-recorded spelling in this reading group contain both 万 and 葉Given nameKazuha
かずは
葉万子
1 source-recorded spelling in this reading group contain both 万 and 葉Given nameHamako
はまこ
万奈葉
1 source-recorded spelling in this reading group contain both 万 and 葉Given nameManaha
まなは
万葉子
1 source-recorded spelling in this reading group contain both 万 and 葉Given nameMayoko
まよこ
万葉香
1 source-recorded spelling in this reading group contain both 万 and 葉Given nameMayoka
まよか
万葉
1 source-recorded spelling in this reading group contain both 万 and 葉Given nameMaha
まは
万葉奈
1 source-recorded spelling in this reading group contain both 万 and 葉Given nameMahana
まはな
万梨葉
1 source-recorded spelling in this reading group contain both 万 and 葉Mariha
まりは
Evidence boundary
Co-occurrence is not popularity or etymology
The pair relation comes from exact JMnedict source rows through the compact kanji-usage index. KANJIDIC2 contributes character metadata only. A high corpus count can reflect dictionary coverage and should not be read as a national usage frequency.