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.

実

Jōyō · KANJIDIC grade 3 · 8 strokes

reality, truth, seed

惠

Jinmeiyō · KANJIDIC grade 10 · 12 strokes

blessing, grace, favor

Find exact-kanji names →

Source rows containing both15

Distinct written forms14

Given-name readings11

Surname readings0

Adjacent 実惠 forms7

Adjacent 惠実 forms6

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

喜実惠

Kimie

きみえ

3 source-recorded spellings in this reading group contain both 実 and 惠Given name

千惠実

Chiemi

ちえみ

3 source-recorded spellings in this reading group contain both 実 and 惠Given name

惠実子

Emiko

えみこ

1 source-recorded spelling in this reading group contain both 実 and 惠Given name

惠実

Emi

えみ

1 source-recorded spelling in this reading group contain both 実 and 惠Given name

二実惠

Fumie

ふみえ

1 source-recorded spelling in this reading group contain both 実 and 惠Given name

惠実

Megumi

めぐみ

1 source-recorded spelling in this reading group contain both 実 and 惠Given name

実惠

Mie

みえ

1 source-recorded spelling in this reading group contain both 実 and 惠Given name

実惠子

Mieko

みえこ

1 source-recorded spelling in this reading group contain both 実 and 惠Given name

実佐惠

Misae

みさえ

1 source-recorded spelling in this reading group contain both 実 and 惠Given name

祐実惠

Yumie

ゆみえ

1 source-recorded spelling in this reading group contain both 実 and 惠Given name

八惠実

Yaemi

やえみ

1 source-recorded spelling in this reading group contain both 実 and 惠

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.