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Revising Custom Tags in Use

clareqiao — Sat, 03 Nov 2018 21:17:37 GMT

If you have used your custom tags to mark up a text, but then want to revise them, a video made by Wu Ruei-Ming 吳瑞明 as part of the Drugs across Asia project can be of reference value. As the video cannot be uploaded here, we have taken some screenshots to show how they did it. The video was recorded in the 正體中文 version of MARKUS.

On the left side of the screenshot below is shown the text that has been marked up. Now, the user wants to change the five bilingual tags on the right into monolingual (Chinese) ones.

Basically, the logic behind the method shown in the video is to add five Chinese tags whose colors correspond to the ones they are meant to replace and then delete the bilingual ones. Here are the specific steps:

Click “管理標記”. In the window that pops up, change the tag names (標記名稱) of these five bilingual tags from following the earlier naming pattern of English translation + transliteration into just English. For instance, for the tag “DrugName 藥名”, delete “_LueMing”.

Having done this with all five, click “確定”. The five tags under revision now appear uncolored.

Click “管理標記” again, this time to change their button names (按鈕名稱) from being bilingual into just Chinese. For instance, for the tag “DrugAction藥效”, delete “DrugAction”.

After having done this with all five, click “確定” and you’ll see in place of the five earlier bilingual tags, there now appear five Chinese ones.

Now let’s color them. Click “管理標記”. In the “新增標記” section of the popup window, for each of the five uncolored tags, copy its tag and button names into corresponding boxes and choose the same color as that for the tag it is going to replace. For example, choose crimson for the tag “藥名”. Then click “新增”.

Now there appear two crimson tags.

The next step is to delete the one you don’t want any more. Click “管理標記” again. In the window that pops up, delete the tag “DrugName 藥名”.

Click “確定” and you’ll see there is but one crimson tag “藥名”, which marks up all the named entities in the text that were previously marked up by the tag “DrugName 藥名”.

This completes the revision of this tag. Do the same for the other four tags, until you have revised them all.

Jiyan Qiao, PhD candidate, Leiden University

Overlapping Tags

dknorr — Mon, 29 May 2017 07:16:48 GMT

I was curious about possibilities for tagging text in such a way that tags overlaps. For example, I'm tagging titles of poems, but some of these also include names of individuals or places that I also want to tag. This works in some cases but not others. (i.e. after tagging a string of text and highlighting a string within that tag, the option to add another tag is not available.) I'm not sure if this is a case of a bug, limited functionality, or me trying to do something that isn't really sensible in the first place.

Tagging Quotations with MARKUS

gabe — Mon, 10 Apr 2017 15:19:38 GMT

In 2015, I started using MARKUS to mark up textual passages that I had to translate for my MA thesis. The built-in ability to identify place names, official titles, personal and alternative names, reign periods, and its easy-to-use interface make it one of the best online platforms for Sinologists who rely on texts in Classical Chinese. While the identification is not always spot on – you still need to use your brain – the identification errors can be easily spotted and manually corrected. And it’s not as time-consuming as tagging everything manually. Since last summer I have been working on a new research project about Tang emperors and have been using a few specific functions in MARKUS to select the passages that I want to analyse. In this blog, I want to share my most recent experiences with manual tagging. At the moment I am collecting direct speech quotes from emperors in a text I am familiar with, the Tang guoshi bu 唐國史補 [Supplement to the History of the Tang]. I could read the text line by line and make notes along the way, but this is very time-consuming. With the use of MARKUS, I can easily filter textual passages with direct speech quotes that are useful for my research, and skip the ones that are not useful because they do not contain speech quotes. Finally, I will export the results to Excel to do further analysis. To search for all the direct speech quotes in a text I have made use of the ‘Keywords helper’ function in MARKUS. With the ‘Keywords helper’ function, MARKUS can tag keywords or characters between certain keywords or characters. Since my text is punctuated, I can easily search for quotations by scanning for double quotation marks (『』). Everything between these two marks should be a quotation (if your text is punctuated, but does not include quotation marks, you can still search for other characters [e.g. 曰 and。]). I have set the minimum of characters to 1 to include even the smallest quotations.

After hitting ‘Ready to markup’ I tagged these keywords (quotes) under a new tag name by clicking on ‘Submit keywords’.

This is the result when only the newly created tag ‘quotes’ is visible:

Since I have also tagged personal names, it is now easy to select only the passages in which certain emperors are mentioned with the ‘passage selection’ function. For this example I selected only one specific id: 19244 (Emperor Xuanzong), but it is also possible to select multiple ids.

After clicking on ‘filter’ only the passages with the specific id of Emperor Xuanzong (in a slightly bigger font size) are shown:

In manual mode, I identified the direct speech quotes from Xuanzong by giving the tag-id the name of the person who is speaking:

I did the same for quotes from other Tang emperors in this text (Daizong 代宗, Dezong 德宗, and Huizong 憲宗). I then exported all the tags to Excel by clicking on the ‘tag summary’ button. I chose to include 10 characters before and after each tag to include information about who is speaking before I clicked on ‘XLSX (MS Excel, testing)’.

In Excel, the results after sorting on type (column 'B') and id (column 'C') are as follows:

With MARKUS, I was able to quickly search all the direct speech quotes, filter all the quotations and manually ID the quotes. Ultimately the tags were exported to Excel. Now the same can be done for other texts for further analysis and comparison.