Development Overview

This page has everything you need to know to teach LanguageTool new error detection rules, plus more. You don’t even have to be a programmer for that.

The three-minute introduction

This section tells you in a nutshell how to write your own LanguageTool rules for detecting errors (see this overview for how many rules LanguageTool already knows for your language):

    <rule id="EXAMPLE_RULE" name="My example rule">
        <message>Did you mean <suggestion>bicycle</suggestion>?</message>
        <example correction="bicycle">My <marker>foo bar</marker> is broken.</example>
        <example>My car is broken.</example>

That’s it! You have just added a new rule. Keep on reading to get a grasp on what the elements of a rule mean and how to build more complex rules or use the rule creator to build simple rules. Check out the text analyzer to get an understanding of how LanguageTool analyzes text internally. Send us your rules so we can add them to the next release of LanguageTool.

Help wanted!

We’re looking for people who support us writing new rules so LanguageTool can detect more errors. Also see the list of supported languages.

How can you help?

If your language isn’t supported yet, you can add it by following the documentation in our wiki.

Source code checkout

If you are a Java developer and you want to extend LanguageTool or if you want to use the latest development version, check out LanguageTool from github:

git clone

Note that due to the embedded dictionaries our git repository is quite large (>800MB), so cloning might take some time. You can then build the code with mvn clean package or just run the tests with mvn clean test. You need at least Java 8 for building LT. Maven’s default memory settings are often too low, so you will probably need to set your environment variable MAVEN_OPTS to:


After the build, the LibreOffice/OpenOffice extension can be found in languagetool-office-extension/target (named *.zip, rename it to *.oxt), the stand-alone version in languagetool-standalone/target (in a sub directory named e.g. LanguageTool-5.0-SNAPSHOT/ - you cannot run the *.jar directly in the target directory). See Maven tips for hints on how to build faster.

Language checking process

This is what LanguageTool does when it analyzes a text for errors:

  1. The text is split into sentences
  2. Each sentence is split into words
  3. Each word is assigned its part-of-speech tag(s) (e.g. cars = plural noun, talked = simple past verb)
  4. The analyzed text is then matched against the built-in Java rules and against the rules loaded from the grammar.xml file

The most important thing you need to keep in mind is that LanguageTool’s rules describe what errors look like, not what correct sentences look like (this is the opposite of how you learn a new language).

Adding new XML rules

Most rules are contained in rules/xx/grammar.xml, whereas xx is a language code like en or de. In the source code, this folder will be found under languagetool-language-modules/xx/src/main/resources/org/languagetool/; the standalone GUI version contains them under org/languagetool/.

A rule is basically a pattern which shows an error message to the user if the pattern matches. A pattern can address words or part-of-speech tags. Here are some examples of patterns that can be used in that file:

A pattern’s tokens are matched case-insensitively by default. This can be changed for the whole pattern or for a single token by setting case_sensitive="yes".

Alternatively, case-sensitive matching can be turned on for single tokens by using (?-i) in regular expressions (ex: <token regexp="yes">(?-i)Bill</token> will match Bill but not bill).

A simple example

Here’s an example of a complete rule that marks bed English, bat attitude etc as an error:

    <rule id="BED_ENGLISH" name="Possible typo 'bed/bat(bad) English/...'">
            <token regexp="yes">bed|bat</token>
          <token regexp="yes">English|attitude</token>
        <message>Did you mean <suggestion>bad</suggestion>?</message>
        <example correction="bad">Sorry for my <marker>bed</marker> English.</example>

The basic elements of a rule

A short description of the elements and their attributes:

Testing rules

The LanguageTool user interface (languagetool.jar) needs to be restarted if you have changed the grammar.xml file. Testing rules is faster with our embedded test case feature: just call sh en on Linux or testrules.bat en on Windows, using your language code instead of en.

This will test your rule with its example sentences: the incorrect sentence is supposed to be detected by your rule, while the correct sentence is not supposed to give an error. If that is not the case you will get a message. In that case, either your rule or your example sentences are not quite right yet.

Using is not only much faster than manually starting the user interface over and over again, it will always test all rules, so we recommend you use that during rule development.

Avoiding the disambiguator

If you want to match the original part-of-speech tags - those not modified by the disambiguator - use raw_pos="yes" on the <pattern>.

Regular Expressions

Alternatively to <pattern><token>...</token></pattern> it’s sometimes easier to write a rule with a traditional regular expression:

    <rule ...>
      <regexp>half an our</regexp>
      <message>Did you mean <suggestion>half an hour</suggestion>?</message>

It’s important to note that this will not care about tokens, it just searches the regular expression per sentence. So this example would also match behalf an our and half an ourselves (which are probably also errors, but not the ones the rule is looking for). To avoid this, you’ll need to specify boundaries with \b, for example <regexp>\bhalf an our\b</regexp>.


You cannot use <regexp> to look for specific POS tags. For that, you can always use the regexp="yes" attribute on a <token> and combine it with the postag or postag_regexp attribute.

You cannot use <antipattern> with <regexp>, but starting with LanguageTool 5.2, you can use RegexAntiPatternFilter to avoid false alarm like this:

<regexp mark="1">(fo.) (bar)</regexp>
<filter class="org.languagetool.rules.patterns.RegexAntiPatternFilter" args="antipatterns:fou"/>

This would match regexp (fo.) (bar), but not fou bar. It’s somewhat limited, as the regex cannot contain spaces. There can be more than one regex like this: args="antipatterns:regex1|regex2|regex3" - i.e. the pipe (|) is used to delimit several regex. For the antipatttern to match, it’s enough if it partially overlaps the match of the <regexp>.


The inflected attribute of the token element is used to match not only the given word but also all of its inflected forms. For example <token inflected="yes">bicycle</token> will match bicycle, bicycles, bicycling etc.

Grouping rules

Sometimes it requires more than one rule to find all occurrences of an error. You can put all those rules in one rulegroup element. The rulegroup’s id and name attribute will be used for all the rules of that group. Overlapping matches for rules in the same rulegroup are filtered out to avoid duplicate matches for the same error.


You cannot address spaces or whitespace directly in a <pattern>. To do so, either use <regexp> (see “Regular Expressions” above), or use spacebefore="yes" to check whether there’s a space between the previous and the current token.


The rules are best put into categories that describe their purpose, and allow to enable or disable a number of rules at the same time. When creating a category, you can use the type attribute to describe the type of the error according to the Quality Issue Type from the W3 Internationalization Tag Set. This will make integration of LT with other tools easier.

Turning rules off by default

Some rules can be optional, useful only in specific registers, or very sensitive. You can turn them off by default by using the attribute default="off". The user can turn the rule on/off in the Options dialog box, and this setting is being saved in the configuration file.


Sometimes exceptions to rules require multiple tokens with complex interrelations. In such a case, one may use an antipattern:

          <example>text word1 word2 more text</example>

This rule would match “This is a word1” but not “This is a word1 word2”. You can use all subelements of pattern in antipattern but phrase and or. The text matched by the antipattern needs to overlap the text matched by the pattern for the antipattern to become active.

The optional examples are used to check that the rule doesn’t match for these example sentences. Please note it is not checked whether it is this specific antipattern that prevents a match.

Antipatterns may be added to a group of rules (and then they are valid for all rules in the group) and for particular rules in a group.

Be aware that if there is or in the pattern this can also lead to problems with antipattern matching (as of LT 5.1).


To match a token optionally, use the min attribute with a value of 0. For example, to match a person or a nice person:

    <token min="0">nice</token>

You can combine this with max to specify the maximum number of occurrences possible. For example, to match a person, a nice person, or a nice nice person:

    <token min="0" max="2">nice</token>

Use max="-1" to match an unlimited number of occurrences.

<or>, <and>

or can be used to match a token if one or both of two conditions are matched. This is sometimes a more compact alternative to writing more than one rule. For example, this would match t walk (as in don’t walk) as well as do not walk:


and can be used to check that a token matches more than one condition. For example, this would only match if a token has both TAG_A and TAG_B:

      <token postag="TAG_A"/>
      <token postag="TAG_B"/>


The skip attribute of the token element is used in two situations:

Simulate a simple chunker for languages with flexible word order, e.g., for matching errors of rection; we could for example skip possible adverbs in some rule. skip="1" works exactly as two rules, i.e.

    <token skip="1">A</token>

is equivalent to the pair of rules:

    <token/>  <!-- this will match any word -->

Using a negative value, we can match until the B is found, no matter how many tokens are skipped. This cannot easily be encoded using empty tokens as above because the sentence could be of any length.

Match coordinated words, for example to match both … as well as we could write:

    <token skip="-1">both<exception scope="next">and</exception></token>

Here the exception is applied only to the skipped tokens.

The scope attribute of the exception is used to make the exception valid only for the token the exception is specified (scope="current") or for skipped tokens (scope="next"). Default behavior is scope="current". Using scopes is useful where several different exceptions should be applied to avoid false alarms. In some cases, it’s useful to use scope="previous" in rules that already have skip="-1". This way, you can set an exception against a single token that immediately precedes the matched token. For example, we want to match tak after jak which is not preceded by a comma:

    <token skip="-1">jak</token>
    <token>tak<exception scope="previous">,</exception></token>

In this case, the rule excludes all sentences, where there is a comma before tak. Note that it’s very hard to make such an exclusion otherwise.


You can refer to previously matched tokens in the pattern. For example:

      <token regexp="yes" skip="-1">ani|ni|i|lub|albo|czy|oraz<exception scope="next">,</exception></token>
      <token><match no="0"/></token>

This rule matches sequences like ani… ani, ni… ni, and i… i (with no comma in between) but you don’t have to write all these cases explicitly. The first match (matches are numbered from zero, so it’s <match no="0"/>) is automatically inserted into the second token. Note that this rule will match sentences like:

Nie kupiłem ani gruszek ani jabłek. Kupię to lub to lub tamto.

A similar mechanism can be used in suggestions, however there are more features, and tokens are numbered from 1 (for compatibility with the older notation \1 for the first matched token). For example:

    <suggestion><match no="1"/></suggestion>

A more complicated example:

      <token regexp="yes">^(\p{Lu}{2}+[i]*\p{Lu}+[\p{L}&amp;&amp;[^\p{Lu}]]{1,4}+)</token>
    <message>Prawdopodobny błąd zapisu odmiany; skrótowce odmieniamy z dywizem: <suggestion><match
        no="1" regexp_match="^(\p{Lu}{2}+[i]*\p{Lu}+)([\p{L}&amp;&amp;[^\p{Lu}]]{1,4}+)"

This rule matches Polish inflected acronyms such as SMSem that should be written with a hyphen: SMS-em. So the acronym is matched with a complicated regular expression, and the match replaces the match using Java regular expression notation. Basically, the regular expression only shows two parts and inserts a hyphen between them.

For some languages (currently Polish, English, Catalan, Spanish, Galician, Dutch, Romanian, Slovak, Russian, Greek, and Ukrainian), element match can be used to insert an inflected matched token (or another word with a specified part of speech tag). For example:

     <token regexp="yes">has|have</token>
       <token postag="VBD|VBP|VB" postag_regexp="yes">
         <exception postag="VBN|NN:U.*|JJ.*|RB" postag_regexp="yes"/>
     <token><exception postag="VBG"/></token>
    <message>Possible agreement error - use past participle here: <suggestion><match
        no="2" postag="VBN"/></suggestion>.

The above rule takes the second verb with a POS tag VBD, VBP or VB and displays its form with a POS tag VBN in the suggestion. You can also specify POS tags using regular expressions (postag_regexp="yes") and replace POS tags – just like in the above example with acronyms. This is useful for large and complicated tagsets (for many examples, see the Polish rule file: rules/pl/grammar.xml).

Sometimes the rule should change the case of the matched word. For this purpose, you can use case_conversion attribute values: startlower, startupper, allupper, alllower and firstupper.

startlower converts only the first character to lowercase and leaves the rest unaltered, e.g. EXAMPLEeXAMPLE.
startupper converts only the first character to uppercase and leaves the rest unaltered, e.g. exampleExample.
allupper converts all characters to uppercase, e.g. eXaMpLeEXAMPLE.
alllower converts all characters to lowercase, e.g. eXaMpLeexample.
firstupper converts the first character to uppercase and the remaining ones to lowercase, e.g. eXaMpLeExample.

Another useful thing is that match can refer to a token, but apply its POS to another word. This is useful for suggesting another word with the same part of speech. There is a special abbreviated syntax used for this purpose:

    <match no="1" postag="verb:.*perf">kierować</match>

This syntax means: take the POS tag of the first matched token that matches the regular expression specified in the postag attribute, and then apply this POS tag to the verb kierować. This way the verb will be inflected just the way the matched verb was originally inflected. The reason why you need to specify the POS tag is that the matched token can have several POS tags (several readings).

Note that by default match element inside the token element inserts only a string – so it matches a string, and not part of speech tags. So even if it refers to a token with a POS tag, it copies the matched token, and not its POS token. However, you can use all above attributes to change the form of the token.

You can however use the match element to copy POS tags alone but to do so, you must use the attribute setpos="yes". All other attributes can be applied so that the POS could be converted appropriately. This can be useful for creating rules specifying grammatical agreement.

You can use postag_replace to require the suggestion to have only some of the same POS tags as the matching word. As always with regular expressions, you put the relevant parts in parenthesis and then refer to them using $1, $2 etc:

    <match no="1"

It should be noted that the token matching the pattern has to match the pattern in the suggestion. If the expression is not the same a runtime exception error can occur (see more information on runtime exception errors here.


LanguageTool supports RuleFilter as a way to make rules more powerful by combining XML syntax and Java code. A RuleFilter takes a rule match from an XML pattern rule and filters it, i.e. it either keeps it as it is, modifies it, or discards it. In XML, the filter is used like this:

      <token regexp="yes">\d</token>
      <token regexp="yes">\d\d</token>
    <filter class="org.languagetool.rules.en.MyFilter" args="myToken:\1 otherArg:\2"/>

In Java code, org.languagetool.rules.en.MyFilter implements the RuleFilter interface with its acceptRuleMatch(...) method. It gets the rule match and the arguments from the args attribute (with \1 etc being resolved to the matching token at that position) as a Map. If it returns null, the rule match will be discarded. If it returns a new rule match, that will be shown to the user. It can also simply return the rule match it gets as a parameter to accept the match.

Repetition rules

Sometimes we want a rule to match only when a pattern has occurred several times in a text. To do this, we would need, in general, a Java text-level rule. But we have added some settings to XML pattern rules in order to do it using only pattern rules.

These settings can be added to a rule or to a rulegroup (but not simultaneuously to a rulegroup and to rules inside this rulegroup). If used in a rulegroup, a match of any of the rules inside the rulegroup will be considered a repetition.

    <rule min_prev_matches="2" distance_tokens="80">
        <token inflected="yes">test</token>
      <message>Repeated word.</message>
      <example correction="">test</example>

This rule will match only when there are at least 2 previous matches within a total distance of 80 tokens (80 tokens from first match to last match). If distance_tokens is not specified, the default value is 60 tokens for min_prev_matches="1", 120 tokens for min_prev_matches="2", 180 tokens for min_prev_matches="3", and so on.

Adding new Java rules

Rules that cannot be expressed with a pattern in grammar.xml can be written with Java code. As a developer, extend LanguageTool’s Rule class and implement the match(AnalyzedSentence) method. If your rule doesn’t work on the sentence level, implement TextLevelRule instead.

See for a simple example which you can use to develop your own rules. You will also need to add your rule class to the getRelevantRules() method in <YourLanguage>.java to activate it. If you’re using the LanguageTool API, you can call JLanguageTool.addRule() instead.

Translating the user interface

We use WebTranslateIt to translate our property files. Updated translations are only copied to the LanguageTool source before a release, so if you need an early preview, say so on the LanguageTool forum and we’ll update the files accordingly.