Developing robust rules

In order to obtain robust, heavily tested rules there are some tips you can follow. Please feel free to improve these if you think you have a good idea. If you don't know how to develop rules yet, please see our development documentation first.

The Easy Way

When developing rules, you should test them. The more you test them, the better - but the following two ways to test rules are easy and effective: using the rule editor on our homepage and testing a local Wikipedia dump.

The Rule Editor

We offer the rule editor on our homepage. You can use it to create a simple rule, or you can switch it to "Advanced mode" to test an existing rule. It will run your rule against a part of Wikipedia. It might find real errors in Wikipedia, but its main use is to find false alarms that your rule would trigger. If your rule matches text which is actually correct, please try to make the rule more strict to avoid such cases as far as possible.

Local Plain Text Checks

If you have a developer setup (Java and Maven), you can use languagetool-standalone/scripts/ Change to the directory the script is in and call it. It will print its usage. Call it with the needed parameters, make changes to the LanguageTool rules and/or source code, and run the script again with the same parameters. It will print a diff of the old versus the new results. This way you can easily spot any newly introduced false alarms. All this requires is a large plain text file that you can LanguageTool to run on (for example from

Local Wikipedia Checks

To check your rule against a larger set of Wikipedia documents, download the LanguageTool-wikipedia-...-snapshot from our nightly builds. Unzip it and run

java -jar languagetool-wikipedia.jar

This will display the usage. For now, check-data is the interesting option for us. You can get its usage by calling

java -jar languagetool-wikipedia.jar check-data

Now download a dump from - this is the URL for German dumps, simply replace "de" in the URL with the code of the language you are interested in. The file we suggest to use is "dewiki-latest-pages-articles.xml.bz2" (again, with your language code instead of "de"). Unpack the dump.

Now, to check a rule with ID MY_RULE, you can use a command similar to this:

java -jar languagetool-wikipedia.jar check-data -l de -f dewiki-20141006-pages-articles1.xml -r MY_RULE --max-errors 100

As always, replace de with the language code you are working with. This command will check the articles from the dump against rule MY_RULE and stop after 100 matches.


  • Some Wikipedias are huge. For those, checking your rule against the whole dump might not be feasible, so feel free to set a limit for the maximum number of articles to be checked (see the command's usage).
  • Text extraction from Wikipedia is not very robust yet. Thus using this approach for rules that check correct use of whitespace or special characters is probably not advisable.
  • You can specify the -f option more than once. Typically, to complement the encyclopedic style of Wikipedia, you would specify the downloadable file from Tatoeba: You need to unpack it and filter out the lines that contain the language you're interested in, e.g. using grep -P "\teng\t" sentences.csv to get the English sentences.

The Long Way

While the tests described above are easy and very useful, they only cover Wikipedia text. It's better to test your rule against a more diverse set of texts. We now describe how to do that.

Get a meaningful corpus collection

Try to obtain several texts regarding diverse subjects like Philosophy, Laws, Maths, Chemistry, Engineering, and so on. Find novels of a variety of genres, like mystery, love, science fiction, humour… It's advisable to gather also articles and other short text elements, in order to perform quick level 1 tests.

There are several sites with free books, like You can find sample texts in plain text files, odf or doc format files and in pdf format files. Working with plain text files is easier, over all for test automation. Therefore I recommend converting files to plain text.

From within LibreOffice/OpenOffice, you can perform the doc/odf/rtf conversion easily. For pdf files you can use pdftotext, a free utility included in many Gnu/Linux distros and also available for Windows.

Use a separate rule file

In LanguageTool you can find your language rule file in org/languagetool/rules/xx/grammar.xml, whereas xx is a language code like en or de. This is the default rule file and it is the file LanguageTool will load when you run it. But it could come in handy if you create a separate xml file containing rules under development. This practice brings to you some advantages:

  • You always work with a small set of rules, regardless the size of the language grammar.xml file.
  • You can compare performances of different approaches to the same problem.
  • The grammar checker performs faster.

By now this is only supported by the stand-alone GUI (languagetool.jar). When needed, load the work file rules-xx-Actual.xml (see below) and test against your typing or short files.

Create example files

Since you can feed LanguageTool text files from command, it is a good idea to set up some files containing example sentences. For each rule or rule group, create a "should warn" file and a "should not warn" file. Each file containing only one sentence per line. This way, you would obtain results like

11.) Line 11, column 9, Rule ID: TU_VERBO_P2[1]
Message: El pronombre personal 'tú' lleva tilde.
Suggestion: tú
.... Si encuntras algo, tu me lo dices. Ellos y tu tenéis mucho de que hablar. Tu primo es igua...

12.) Line 12, column 23, Rule ID: TU_FINAL[4]
Message: El pronombre personal 'tú' lleva tilde.
Suggestion: tú
...s mucho de que hablar. Tu primo es igual que tu. Yo lo se todo sobre ti. Tuve que aprender a...

and it would be very easy to see if it worked as expected. Of course using the "should not warn" file the output expected would be something like

Expected text language: Spanish
Working on texts/dequeismos-bien.txt...
Time: 1153ms for 25 sentences (21.7 sentences/sec)

Sometimes, for some simple rules it isn't worth to make two files, one file should be enough. Be sure to put the correct examples at the tail of the file to preserve the line->error number correlation.

You can use these files as an input for LanguageTool command line.

Development model

1) Choose the rule you want to implement or improve

  • Search the rule you are thinking on. It may be already implemented, or perhaps it is a particular case of another rule that have to be extended.
  • Be sure the rule you choose is computable. There are some rules relying on meanings, like ambiguous constructions.
  • Try to avoid rules with extremely low incidence. They waste computer resources and they may help only 1 out of 100.000 users.

2) Design the rule using a rule or rule group

Tend to make it general. If the rule is complex enough, create a separate XML file containing the new XML rules.
To do this, use the actual grammar.xml file as a template:

<?xml version="1.0" encoding="UTF-8"?>
<?xml-stylesheet type="text/xsl" href="../print.xsl"  title="Pretty print" ?>
<?xml-stylesheet type="text/css" href="../rules.css"  title="Easy editing stylesheet" ?>
<rules lang="es" xsi:noNamespaceSchemaLocation="../rules.xsd" xmlns:xsi="" xmlns:xs="">
  <!-- Here goes the stuff -->

and update language code. Let's use xx as a language code. I also like to move the file, so update the stylesheet paths if applicable. For example:

<?xml version="1.0" encoding="UTF-8"?>
<?xml-stylesheet type="text/xsl" href="rules/print.xsl" title="Pretty print" ?>
<?xml-stylesheet type="text/css" href="rules/rules.css" title="Easy editing stylesheet" ?>
<rules lang="xx" xsi:noNamespaceSchemaLocation="../rules.xsd" xmlns:xsi="" xmlns:xs="">
  <!-- here goes the stuff -->

Now save the file. In order to use it with languagetool.jar, use a name like rules-xx-Actual.xml. Load this rule file from the "File" menu. Now you can work with your small rule set.

Search for use cases and write them down to files

  • Search for different cases matching the rule. Write them to "should warn" file
  • Search for cases which may fool the rule. Write them to "should not warn" file or at the end of the unique file, if it was your choice.

Greedy - Lazy balancing

Making a greedy rule set, testing it against the corpus collection and saving the results is always a great idea. Later you can compare if the fine tuned rule matched all the cases in such corpus.

For example, if you want to implement the "All to gather" rule ("All together") in a first stage you can make a rule with the tokens All and to. Perhaps, and surprisingly you can improve the rule because you found "All to getter".

3) Test the rule using languagetool.jar.

languagetool.jar is a very quick way to test if you last modification went well.
Don't forget to choose your development file! Step back until satisfied.

4) Test the rule against your short "should warn" file and a "should not warn" files.

Keep the output for future reference. You may fix some cases but break some others when changing rules!
Return to step 2 if unsatisfied.

You can automate this step, but keep in mind languagetool-commandline.jar does not accept the trick of the separate file. In order to avoid putting under risk your old grammar.xml file, you can use the sample xx language.

5) Integrate/replace your new rules into the regular grammar.xml file and run (Linux) testrules.bat (Windows).

This step is very important because you can find many problems with the examples included in your rules. You can also detect errors like unmarked regular expressions.
Once or testrules.bat is run, you're ready to test your rules against your corpus collection. Call the script with your language code as a parameter to run only the tests relevant to your language, e.g. ./ en for English tests. This is much faster than running all tests.

6) Test the rules against your level 1 corpus collection.

This is the same procedure as step 4 but using your short articles. It will take a little more time than the above step but not as much as the heavy corpus. It will raise a couple of false alarms but you'll have to wait less when correcting them.
You can automate this with a very simple shell script. This sample is based upon you have all the texts in a directory called texts and they have the same prefix lt- (for long text):

# Long test for Spanish grammar
# Copyright (C) 2010 Juan Martorell

  echo "$0 {level}"
  echo '  where {level} is one of'
  echo '       1: Test level 1 corpus: files prefixed with lt-1-'
  echo '       2: Test level 2 corpus: files prefixed with lt-2-'
  echo '       a: Test all levels'

function process {
for file in $FILELIST
        echo "Processing $file"
        java -jar languagetool-commandline.jar --language es \
         $file >$file.log    

if [ -z "$1" ]; then
elif [ "$1" == "1" ]; then
  FILELIST=`ls -rS texts/tl-1-*.txt`
elif [ "$1" == "2" ]; then
  FILELIST=`ls -rS texts/tl-2-*.txt`
elif [ "$1" == "a" ]; then
  FILELIST=`ls -rS texts/tl-?-*.txt`
elif [ "$1" == "--help" ]; then
  echo "** $1 is not a valid option."

Notice there are some rules disabled. They are typical of PDF->TXT conversion and usually they don't supply value — in fact they are annoying if they are not under test.

7) Test the rules against your level 2 corpus collection.

Once you are satisfied with the level 1 test result, it's time to test it against at least 1.000.000 words. It will take time, but after this test, you'll be reasonably sure you have false alarms under control.

8) Test the regular rule file against your level 2 corpus collection.

This is the final test. Like you did in step 5, copy the rules into the regular grammar.xml file and run the tests against the level 2 corpus (and also level 1 if you want to be more rigorous) You can use a script like this:

# Complete test for Spanish grammar
# Copyright (C) 2010 Juan Martorell

function scancorpus {
for file in `ls -rS texts/tl-*.txt`
        echo "Processing $file"
        java -jar languagetool-commandline.jar --language es --mothertongue en $file >$file.log        

Here you can do some benchmarking if you saved the results prior to the new rules integration. For example I have a corpus of roughly 1.7 million words and it takes for me about 14 minutes, with an average speed of 100 sentences per second.

This is also a good moment to ensure there are not overlapping rules.

Anyway, the most important thing is that this way you make sure the whole thing works as expected.

9) Release the regular file

Update git or send your file to your language maintainer when you are sure the quality is OK.


  • Try to automate the developing process. It will take some time, but it is time you'll save in the long way.
  • This development method is optional and of course you can use it at your will, any step can be adapted to your personal needs and to your language particularities.
Unless otherwise stated, the content of this page is licensed under Creative Commons Attribution-ShareAlike 3.0 License