This is the Obsidian vault I created to track my learning of the “Frequently Encountered Words” (FEW) of William Shakespeare’s works.
I have been thinking about learning to read Shakespeare for a while. Watching The Tragedy of Macbeth, an Apple TV+ reinterpretation of the classical story, has only intrigued me more. However, with little prior knowledge of English literature, the archaic vocabulary and twisted grammar turn out to be too demanding for me as an ESL speaker.
One day I discovered by chance ShakespearesWords.com, a great online library of Shakespeare-related resources. Among the “Starting Points” it provided, there is a list of “Frequently Encountered Words,” comprised of 100 words that the editors deem most important. I bookmarked the page outright but failed to find an initiative to actually start learning.
Yesterday, a friend of mine posted on WeChat that she was starting a study group where members would motivate and encourage each other to, well, learn vocabulary. There would be no mandated syllabus; members are expected to bring their own vocabulary book and schedule. The one and only rule is that learning outcomes shall be reported on a daily basis during the monthlong sprint, or the violator would be kicked out.
I signed up for the challenge on a whim and the FEW occured to me while I was thinking about what to learn; a hundred words spreading over thirty-some days sounds a reasonable goal. So I pulled the FEW page, reformatted it into an Obsidian vault — I will explain the process with more details in the coming days — and started to work. Obsidian is my preferred knowledge management software and with the help of built-in and community plugins such as random note and Dataview, it’s trivial to track progress and take notes along the way.
The repo reflects exactly the current status of the said vault on my computer. I will use git commits as daily check-ins. Hopefully it would end up a stuffed database after a month. Public supervision and suggestion are certainly welcomed.
Each day I will use the “random note” feature of Obsidian to pull up three words from the words directory. Then, I will read the definition and example usage, locate the occurence in the original context, and supplement it with a Chinese translation.
For each play referred to in the examples, I will also create an entry in the works directory, in which, among other notes of interest, the corresponding Wikipedia page will be included in form of an iframe embedment for the convenience of future references.
[TO BE COMPLETED]
First, the FEW page was downloaded as a Markdown document with the browser extension MarkDownload, with each word corresponding to an h3 element:
### afeard (adj.)
afraid, frightened, scared
[Cym IV.ii.94](https://www.shakespeareswords.com/Public/Play.aspx?Act=4&Scene=2&WorkId=7#139609) \[Cloten to Guiderius\] *Art not afeard?*
...
### anon (adv.)
soon, shortly, presently
...A full list of words was then retrieved with the regular expression /^### .*$ and saved to a file named LIST .
Next, after some cosmetic fixes (e.g., removing trailing spaces), the long document was split into 100 separate documents with csplit:
csplit -f 'few_' few.md '/^###.*/' {100}The command above would generate a hundred separate files, named few_00 to few_99, with each file containing the definitions and examples for one of the FEW. The filenames were then modified to include the words themselves prepared in advance in LIST. (The vidir command in moreutils and VIM were used to facilitate the renaming.) The resulting few directory looks as follows:
00_afeard.md
01_anon.md
02_apace.md
...
98_wont.md
99_wot.mdDataview is used to create the dashboard (see DASHBD.md) for tracking and reviewing.
Dashview uses an SQL-like syntax for retrieving and presentating notes from the vault. For example, the following block retrieves all notes of which the property learned_on equals to the current date, i.e., it is learned today:
table title as "Title"
from "words"
where learned_on = date(today)
sort title
[TO BE COMPLETED]