Open the app — Index Tagger
Have you ever tagged every personal and place name in a translation manuscript?
Find 慶州, change it to <place>慶州</place>, find the next 慶州, change it again.
Using “Replace All” in a word processor sounds fine until you have a hundred index terms — that’s a hundred rounds.
And sometimes you replace a spot that was already tagged, ending up with <place><place>慶州</place></place>.
So I made this.
Write the list of replacements once as a table, and it sweeps through the whole manuscript and tags everything at once.
Put translated words instead of index terms and you can use it as a simple machine translator.
How to Use
Basic Steps
- Paste your manuscript into the Source Text box.
- Write your replacement list in the Index Conversion Table.
- Click [Tag Index Terms].
That’s it. The result appears in the box below, with colors showing what changed.
Writing the Conversion Table
Separate the original and the replacement with a single tab character.
original[tab]replacement
Like this.
慶州 <place>慶州</place>
李舜臣 <person>李舜臣</person>
It must be a tab, not spaces.
Copying two columns from a spreadsheet inserts tabs automatically, so managing your list in Excel or Google Sheets and pasting it over is the easiest route.
Adding Comments
When the list gets long, even you won’t remember what’s what.
Leave notes with # or //.
# place names
慶州 <place>慶州</place>
// personal names
李舜臣 <person>李舜臣</person>
慶州郡 <place>慶州郡</place> # inline comments work too
Start of the line or the middle, either way.
The :// in http:// or https:// is not treated as a comment, so URLs are safe.
Excluding Parts of the Source
The same rule applies to the source text. Anything after # or // is left alone.
General Yi Sun-sin visited 慶州. # this part is not converted
Handy when you keep editorial notes inside the manuscript while you work.
Options
- Exclude single-character terms : One-character terms catch everything. Register
國and it hits國家,中國, and國民too. Turn this on in that case. (default: off) - Trim whitespace : Copying from a table often drags along leading and trailing spaces. This strips them automatically. (default: on)
Checking the Result
When the conversion finishes, three numbers appear at the bottom.
| Item | Meaning |
|---|---|
| Index terms | How many terms were actually registered |
| Single-character terms | How many of those are one character |
| Replacements | How many times something actually changed |
If you registered 100 terms but only 3 replacements happened, your table doesn’t match the manuscript.
The numbers alone tell you something is wrong.
Results are painted in a different color per tag.
The color wheel is divided evenly by the number of tag types, so no matter how many types you have, each gets a distinguishable color.
Just skimming the page lets you spot where a person and a place got swapped.
Good to Know
How Double Tagging Is Prevented
Suppose you registered both 慶州 and 慶州郡.
Process the shorter one first and 慶州郡 becomes the nonsense <place>慶州</place>郡.
So longer terms are processed first.
Once 慶州郡 is wrapped in a tag, that span is marked as done and 慶州 cannot touch it again.
Just keeping the length order eliminates most accidents.
Errors Caught in Advance
The table is checked before conversion runs. If any of these appear, you get the line number and it stops.
| Error | When it happens |
|---|---|
| No tab | Usually you separated with spaces |
| Two or more tabs | A tab slipped into the replacement value |
| Empty original | Nothing before the tab |
| Empty replacement | Nothing after the tab |
| Conflicting values | The same original given two different replacements |
| Circular reference | The result could get replaced again |
Conflicting values looks like this.
慶州 <place>慶州</place>
慶州 <person>慶州</person> # error: same original, different value
Circular reference looks like this.
慶州 경주
경주 慶州 # error: they replace each other endlessly
When the list runs to hundreds of lines these mistakes hide well.
So they are caught before conversion, and the offending line can be copied with one click.
Hanja Is Matched for You
Sometimes the same Hanja exists under different codes.
You wrote 說 in the table but the manuscript has a different code for 說 — they look identical to you, but the computer sees two different characters.
The tagger normalizes multi-code Hanja automatically so they match, so you don’t have to worry about it.
Duplicate terms in the list are consolidated too.
Upload
Click the Upload button in each app to load text files.
Supported formats: .txt, .md, .html, .xml, .tsv, .csv
Save
Download the converted result with the Save button.
Copy
Copy the result to your clipboard with the Copy button.
Open the app — Index Tagger