mirror of
https://github.com/ClickHouse/ClickHouse.git
synced 2024-12-18 04:12:19 +00:00
284 lines
7.2 KiB
Markdown
284 lines
7.2 KiB
Markdown
---
|
||
slug: /en/sql-reference/functions/nlp-functions
|
||
sidebar_position: 67
|
||
sidebar_label: NLP
|
||
title: "[experimental] Natural Language Processing functions"
|
||
---
|
||
|
||
:::warning
|
||
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
|
||
<lemmatizers>
|
||
<lemmatizer>
|
||
<lang>en</lang>
|
||
<path>en.bin</path>
|
||
</lemmatizer>
|
||
</lemmatizers>
|
||
```
|
||
|
||
## 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
|
||
<synonyms_extensions>
|
||
<extension>
|
||
<name>en</name>
|
||
<type>plain</type>
|
||
<path>en.txt</path>
|
||
</extension>
|
||
<extension>
|
||
<name>en</name>
|
||
<type>wordnet</type>
|
||
<path>en/</path>
|
||
</extension>
|
||
</synonyms_extensions>
|
||
```
|
||
|
||
## 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 │
|
||
└────────────────────────────────────────────────┘
|
||
```
|