Common words

两宋 LiǎngSòng the Song dynasty (960-1279)
刘宋 LiúSòng Song of the Southern dynasties 南朝宋 (420-479), with capital at Nanjing
北宋 BěiSòng the Northern Song Dynasty (960-1127)
南宋 Nánsòng the Southern Song dynasty (1127-1279)
唐宋 TángSòng the Tang (618-907) and Song (960-1279) dynasties
宋代 Sòngdài Song dynasty (960-1279)
宋史 Sòngshǐ History of the Song Dynasty, twentieth of the 24 dynastic histories 二十四史 ÈrshísìShǐ, composed under Toktoghan 脱脱 Tuōtuō in 1345 during the Yuan Dynasty 元 yuán, 496 scrolls
宋书 Sòngshū History of Song of the Southern Dynasties 南朝宋 NáncháoSòng or Liu Song 刘宋 LiúSòng, sixth of the 24 dynastic histories 二十四史 ÈrshísìShǐ, compiled by Shen Yue 沈约 ShěnYuē in 488 during Liang of the Southern Dynasties 南朝梁 NáncháoLiáng, 100 scrolls; (not to be confused with 宋史 Sòngshǐ)
宋朝 Sòngcháo Song Dynasty (960-1279)
宋江 SòngJiāng Song Jiang, a principal hero of the novel Water Margin 水浒传 ShuǐhǔZhuàn

About MyCidian

MyCidian is a free, web-based Chinese-English dictionary designed for native English speakers.

MyCidian is heavily inspired by Jisho.org, my favorite Japanese dictionary website. One of my biggest priorities when designing MyCidian was convenience. I wanted looking up a word to be quick, simple, and actually useful for someone who is learning Chinese.

This project is still ongoing and will only get better. It's free and staying that way. Web only, with no app planned. Ad-free for now; if that ever changes, signing in will remove them.

Some decisions

Recent lookups and your Study List stay in this browser.: MyCidian never receives which words you save, only an anonymous count of star clicks. Your list won't follow you to another device. Clearing site data deletes it, and some browsers, like Safari, may delete it if you don't visit for a while. Export your Study List to keep a copy.
Every alternate form, not a guess: One simplified character can stand for several traditional ones — 发 is both 發 (to send) and 髮 (hair). Picking one to display would look cleaner and lose the distinction.

Where the data comes from

CC-CEDICT: The core dictionary.
Make Me a Hanzi: Stroke order, radicals and character composition.
HSK 3.0 word lists: Proficiency-level browsing, by HSK 3.0 level. A word the 3.0 lists leave out keeps its HSK 2.0 level.
Example sentences: Over 70,000 checked sentences. About 51,000 were written by Qwen3.8-27B running locally; the rest (about 20,000) are older Claude Haiku examples. They were checked by Claude Sonnet, with a native-speaker spot check (94% natural in a 50-sentence sample). A few hundred older, unchecked Haiku examples are still shown where no checked sentence exists.
Claude Haiku: An enrichment pass grouping senses, plus a separate one tagging archaic and literary usage.

Built by Zeb Barrett

Credits

MyCidian is built on several openly licensed datasets. Every one currently in use is credited below, by name, with the licence it ships under.

CC-CEDICT: The core dictionary — headwords, pinyin and English definitions. Source, licensed CC BY-SA 4.0.
Make Me a Hanzi — dictionary data: Character definitions, derived from Unihan and CJKlib. Source, licensed LGPL 3.0.
Make Me a Hanzi — stroke-order graphics: Stroke order animation, radicals and character decomposition, derived from the Arphic PL KaitiM GB and PL UKai fonts. Source, licensed under the Arphic Public License.
hanziDB.csv: Character frequency ranking. Source, licensed MIT.
HSK 3.0 word lists: Proficiency-level browsing, compiled from the public HSK 3.0 standard by two open-source projects: complete-hsk-vocabulary and hsk30, both licensed MIT.
wordfreq: Word frequency ranking, used to put the commoner word first when several entries share a meaning. Compiled by Robyn Speer at Luminoso (version 3.1.1). Source, licensed CC BY-SA 4.0. MyCidian has changed the data: the frequencies are converted to a rank and matched to CC-CEDICT headwords.
The sources behind wordfreq's Chinese list: Wikipedia; OPUS OpenSubtitles 2018, from the OpenSubtitles project; SUBTLEX-CH, freely available data created by Marc Brysbaert et al. (Cai & Brysbaert, 2010); NewsCrawl 2014 and GlobalVoices news text; Google Books Ngrams 2012; web text from OSCAR; Twitter; and the word list distributed with the Jieba word segmenter.