Results, と

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トムTOMU とto メアリーMEARII はha 幸せshiawase そうsou だda。: Tom and Mary seem happy.
私watashi はha 猫neko とto 犬inu をwo 飼っka てte いi ますmasu。: I look after a cat and a dog.
今夜kon'ya はha 早めhayame にni 寝よneyo うu とto 思うomou。: I think I'll go to bed early tonight.
今日kyou はha 早めhayame にni 寝よneyo うu とto 思うomou。: I think I'll go to bed early tonight.
商品shouhin のno 品質hinshitsu にni はha 万全banzen をwo 期しkishi てte おりori ますmasu がga、万一man'ichi 商品shouhin がga 破損hason・汚損oson しshi てte いi たta 場合baai、またはmataha ごgo 注文chuumon とto 異なるkotonaru 場合baai はha、おo 届けtodoke 後go7日nichi 以内inai にni ごgo 連絡renraku くださいkudasai。: We strive for perfection in our products. In the rare case that there is breakage, staining or the order is incorrect, please contact us within seven days of the product's arrival.
友達tomodachi とto 恋人koibito のno 違いchigai ってtte 何nani なna んn だろdaro うu。: What's the difference between a friend and a lover?
紅茶koucha とto コーヒーKOOHII、どっちdotchi がga 好きsuki？: Which do you like better, tea or coffee?
ボストンBOSUTON とto シカゴSHIKAGO、どっちdotchi がga 好きsuki？: Which do you like better, Boston or Chicago?
彼女kanojo はha そのsono 箱hako をwo 持ち上げよmochiageyo うu とto しshi たta がga 無理muri だっda たta。: She tried to lift the box, but found it impossible to do.
一日nichi かka二日nichi でde 終わるowaru とto 思いomoi ますmasu。: I'll be able to finish in a day or two.
フランス語furansugo とto 英語eigo、どちらdochira でde 話すhanasu ことkoto がga 多いooi ですdesu かka？: Which do you speak more often, French or English?
果てhate がga ないnai ものmono はha 二つfutatsu だけdake あるaru。宇宙uchuu とto 人間ningen のno 愚かoroka さsa だda。前者zensha についてnitsuite はha 確かtashika でde はha ないnai がga。: Only two things are infinite, the universe and human stupidity, and I'm not sure about the former.
独りhitori はha 良いyoi ものmono だda。だda がga「独りhitori はha 良いyoi」とto 言うiu にni はha 相手aite がga 必要hitsuyou だda。: Solitude is fine, but you need someone to tell you that solitude is fine.
ボストンBOSUTON とto シカゴSHIKAGO、どちらdochira にni よくyoku 行きiki ますmasu かka？: Where do you go more often, Boston or Chicago?
トムTOMU とto メアリーMEARII、どっちdotchi のno 方hou がga 好きsuki？: Who do you like better, Tom or Mary?
あなたanata がga 詩shi をwo 書くkaku とto はha 知らshira なかっnaka たta。: I didn't know you were a poet.
トムTOMU とto 私watashi のno 間ma にni はha 何nani もmo ないnai わwa。: There is nothing going on between Tom and me.
トムTOMU はha 犬inu をwo 飼っka てte いるiru とto 思っomo てte いi たta。: I thought Tom had a dog.
トムTOMU はha メアリーMEARII がga 料理ryouri がga 好きsuki だda とto 知らshira なかっnaka たta。: Tom didn't know that Mary liked to cook.
定住teijuu しshi てるteru 生活seikatsu するsuru ほとんどhotondo のno イタチITACHI 科ka とto 違っchiga てte、クズリ,KUZURIはha、絶えずtaezu 餌食ejiki をwo 捜しsagashi てte、1500-2000平方キロheihoukiro までmade をwo 占めるshimeru 自分jibun のno 土地tochi のno 上ue でde 歩き回るarukimawaru。: Unlike most of mustelids who lead a settled lifestyle, wolverines constantly wander in search of prey on their individual plots of land occupying up to 1500-2000 square kilometers.
強いtsuyoi 足ashi とto 長いnagai 爪tsume のno おかげokage でde、クズリ,KUZURIはha 簡単kantan にni 木ki にni 登るnoboru ことkoto がga できるdekiru。: Thanks to strong paws and long claws wolverine can easily climb the trees.
しばしばshibashiba、それsore はha オオカミOOKAMI とto 熊kuma のno 餌食ejiki のno 残りnokori をwo 食べるtaberu。: It often eats remains of preys of wolves and bears.
このkono 場合baai 犠牲gisei にni なるnaru のno はha、若いwakai 子ko 牛ushi とto 病気byouki のno 動物doubutsu かka 負傷fushou しshi たta 動物doubutsu だda。: If this is the case, its victims are usually young calves, injured or sick animals.
クズリKUZURIはha 非常hijou にni 有害yuugai なna 野獣yajuu でde あるaru のでnode、熊kuma さえsae、クズリ,KUZURIにni 遭遇souguu するsuru のno をwo 回避kaihi しよshiyo うu とto するsuru。: Since wolverine is a very evil wild beast, even a bear in the case of encountering a wolverine tries to avoid it.
人生jinsei にni 無駄muda なna ことkoto なんてnante 一つhitotsu もmo ないnai とto 思うomou。: I think everything happens for a reason.

Kanji

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© Based on JMdict, KANJIDIC2, and JMnedict, property of the Electronic Dictionary Research and Development Group, used in conformance with the Group's licence. Example sentences from the Tatoeba project (CC BY 2.0). Kanji stroke order data from the KanjiVG project by Ulrich Apel (CC BY-SA 3.0). See comprehensive list of data sources for more info.

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