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.

瑠

Jōyō · KANJIDIC grade 8 · 14 strokes

lapis lazuli

絵

Jōyō · KANJIDIC grade 2 · 12 strokes

picture, drawing, painting

Find exact-kanji names →

Source rows containing both14

Distinct written forms14

Given-name readings11

Surname readings0

Adjacent 瑠絵 forms0

Adjacent 絵瑠 forms12

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

紫絵瑠

Shieru

しえる

2 source-recorded spellings in this reading group contain both 瑠 and 絵Given name

絵瑠奈

Eruna

えるな

2 source-recorded spellings in this reading group contain both 瑠 and 絵Given name

瑠実絵

Rumie

るみえ

2 source-recorded spellings in this reading group contain both 瑠 and 絵Given name

乃絵瑠

Noeru

のえる

1 source-recorded spelling in this reading group contain both 瑠 and 絵Given name

絵瑠

Eru

える

1 source-recorded spelling in this reading group contain both 瑠 and 絵Given name

絵瑠麻

Eruma

えるま

1 source-recorded spelling in this reading group contain both 瑠 and 絵Given name

絵瑠美

Erumi

えるみ

1 source-recorded spelling in this reading group contain both 瑠 and 絵Given name

絵瑠萌

Erumo

えるも

1 source-recorded spelling in this reading group contain both 瑠 and 絵Given name

有絵瑠

Arieru

ありえる

1 source-recorded spelling in this reading group contain both 瑠 and 絵Given name

絵瑠夢

Erumu

えるむ

1 source-recorded spelling in this reading group contain both 瑠 and 絵Given name

絵瑠沙

Eruza

えるざ

1 source-recorded spelling in this reading group contain both 瑠 and 絵

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.