---
slug: /en/sql-reference/functions/nlp-functions
sidebar_position: 67
sidebar_label: NLP
title: "[experimental] Natural Language Processing functions"
---
:::note
This is an experimental feature that is currently in development and is not ready for general use. It will change in unpredictable backwards-incompatible ways in future releases. Set `allow_experimental_nlp_functions = 1` to enable it.
:::
## stem
Performs stemming on a given word.
**Syntax**
``` sql
stem('language', word)
```
**Arguments**
- `language` — Language which rules will be applied. Must be in lowercase. [String](../../sql-reference/data-types/string.md#string).
- `word` — word that needs to be stemmed. Must be in lowercase. [String](../../sql-reference/data-types/string.md#string).
**Examples**
Query:
``` sql
SELECT arrayMap(x -> stem('en', x), ['I', 'think', 'it', 'is', 'a', 'blessing', 'in', 'disguise']) as res;
```
Result:
``` text
┌─res────────────────────────────────────────────────┐
│ ['I','think','it','is','a','bless','in','disguis'] │
└────────────────────────────────────────────────────┘
```
## lemmatize
Performs lemmatization on a given word. Needs dictionaries to operate, which can be obtained [here](https://github.com/vpodpecan/lemmagen3/tree/master/src/lemmagen3/models).
**Syntax**
``` sql
lemmatize('language', word)
```
**Arguments**
- `language` — Language which rules will be applied. [String](../../sql-reference/data-types/string.md#string).
- `word` — Word that needs to be lemmatized. Must be lowercase. [String](../../sql-reference/data-types/string.md#string).
**Examples**
Query:
``` sql
SELECT lemmatize('en', 'wolves');
```
Result:
``` text
┌─lemmatize("wolves")─┐
│ "wolf" │
└─────────────────────┘
```
Configuration:
``` xml
en
en.bin
```
## synonyms
Finds synonyms to a given word. There are two types of synonym extensions: `plain` and `wordnet`.
With the `plain` extension type we need to provide a path to a simple text file, where each line corresponds to a certain synonym set. Words in this line must be separated with space or tab characters.
With the `wordnet` extension type we need to provide a path to a directory with WordNet thesaurus in it. Thesaurus must contain a WordNet sense index.
**Syntax**
``` sql
synonyms('extension_name', word)
```
**Arguments**
- `extension_name` — Name of the extension in which search will be performed. [String](../../sql-reference/data-types/string.md#string).
- `word` — Word that will be searched in extension. [String](../../sql-reference/data-types/string.md#string).
**Examples**
Query:
``` sql
SELECT synonyms('list', 'important');
```
Result:
``` text
┌─synonyms('list', 'important')────────────┐
│ ['important','big','critical','crucial'] │
└──────────────────────────────────────────┘
```
Configuration:
``` xml
en
plain
en.txt
en
wordnet
en/
```
## detectLanguage
Detects the language of the UTF8-encoded input string. The function uses the [CLD2 library](https://github.com/CLD2Owners/cld2) for detection, and it returns the 2-letter ISO language code.
The `detectLanguage` function works best when providing over 200 characters in the input string.
**Syntax**
``` sql
detectLanguage('text_to_be_analyzed')
```
**Arguments**
- `text_to_be_analyzed` — A collection (or sentences) of strings to analyze. [String](../../sql-reference/data-types/string.md#string).
**Returned value**
- The 2-letter ISO code of the detected language
Other possible results:
- `un` = unknown, can not detect any language.
- `other` = the detected language does not have 2 letter code.
**Examples**
Query:
```sql
SELECT detectLanguageMixed('Je pense que je ne parviendrai jamais à parler français comme un natif. Where there’s a will, there’s a way.');
```
Result:
```response
fr
```
## detectLanguageMixed
Similar to the `detectLanguage` function, but `detectLanguageMixed` returns a `Map` of 2-letter language codes that are mapped to the percentage of the certain language in the text.
**Syntax**
``` sql
detectLanguageMixed('text_to_be_analyzed')
```
**Arguments**
- `text_to_be_analyzed` — A collection (or sentences) of strings to analyze. [String](../../sql-reference/data-types/string.md#string).
**Returned value**
- `Map(String, Float32)`: The keys are 2-letter ISO codes and the values are a perentage of text found for that language
**Examples**
Query:
```sql
SELECT detectLanguageMixed('二兎を追う者は一兎をも得ず二兎を追う者は一兎をも得ず A vaincre sans peril, on triomphe sans gloire.');
```
Result:
```response
┌─detectLanguageMixed()─┐
│ {'ja':0.62,'fr':0.36 │
└───────────────────────┘
```
## detectLanguageUnknown
Similar to the `detectLanguage` function, except the `detectLanguageUnknown` function works with non-UTF8-encoded strings. Prefer this version when your character set is UTF-16 or UTF-32.
**Syntax**
``` sql
detectLanguageUnknown('text_to_be_analyzed')
```
**Arguments**
- `text_to_be_analyzed` — A collection (or sentences) of strings to analyze. [String](../../sql-reference/data-types/string.md#string).
**Returned value**
- The 2-letter ISO code of the detected language
Other possible results:
- `un` = unknown, can not detect any language.
- `other` = the detected language does not have 2 letter code.
**Examples**
Query:
```sql
SELECT detectLanguageUnknown('Ich bleibe für ein paar Tage.');
```
Result:
```response
┌─detectLanguageUnknown('Ich bleibe für ein paar Tage.')─┐
│ de │
└────────────────────────────────────────────────────────┘
```
## detectCharset
The `detectCharset` function detects the character set of the non-UTF8-encoded input string.
**Syntax**
``` sql
detectCharset('text_to_be_analyzed')
```
**Arguments**
- `text_to_be_analyzed` — A collection (or sentences) of strings to analyze. [String](../../sql-reference/data-types/string.md#string).
**Returned value**
- A `String` containing the code of the detected character set
**Examples**
Query:
```sql
SELECT detectCharset('Ich bleibe für ein paar Tage.');
```
Result:
```response
┌─detectCharset('Ich bleibe für ein paar Tage.')─┐
│ WINDOWS-1252 │
└────────────────────────────────────────────────┘
```