elasticsearch/docs/reference/elasticsearch-plugins/analysis-nori-tokenizer.md
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---------

Co-authored-by: Liam Thompson <32779855+leemthompo@users.noreply.github.com>
Co-authored-by: Liam Thompson <leemthompo@gmail.com>
Co-authored-by: Martijn Laarman <Mpdreamz@gmail.com>
Co-authored-by: István Zoltán Szabó <szabosteve@gmail.com>
2025-02-27 17:56:14 +01:00

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---
mapped_pages:
- https://www.elastic.co/guide/en/elasticsearch/plugins/current/analysis-nori-tokenizer.html
---
# nori_tokenizer [analysis-nori-tokenizer]
The `nori_tokenizer` accepts the following settings:
`decompound_mode`
: The decompound mode determines how the tokenizer handles compound tokens. It can be set to:
`none`
: No decomposition for compounds. Example output:
```
가거도항
가곡역
```
`discard`
: Decomposes compounds and discards the original form (**default**). Example output:
```
가곡역 => 가곡, 역
```
`mixed`
: Decomposes compounds and keeps the original form. Example output:
```
가곡역 => 가곡역, 가곡, 역
```
`discard_punctuation`
: Whether punctuation should be discarded from the output. Defaults to `true`.
`lenient`
: Whether the `user_dictionary` should be deduplicated on the provided `text`. False by default causing duplicates to generate an error.
`user_dictionary`
: The Nori tokenizer uses the [mecab-ko-dic dictionary](https://bitbucket.org/eunjeon/mecab-ko-dic) by default. A `user_dictionary` with custom nouns (`NNG`) may be appended to the default dictionary. The dictionary should have the following format:
```txt
<token> [<token 1> ... <token n>]
```
The first token is mandatory and represents the custom noun that should be added in the dictionary. For compound nouns the custom segmentation can be provided after the first token (`[<token 1> ... <token n>]`). The segmentation of the custom compound nouns is controlled by the `decompound_mode` setting.
As a demonstration of how the user dictionary can be used, save the following dictionary to `$ES_HOME/config/userdict_ko.txt`:
```txt
c++ <1>
C쁠쁠
세종
세종시 세종 시 <2>
```
1. A simple noun
2. A compound noun (`세종시`) followed by its decomposition: `세종` and ``.
Then create an analyzer as follows:
```console
PUT nori_sample
{
"settings": {
"index": {
"analysis": {
"tokenizer": {
"nori_user_dict": {
"type": "nori_tokenizer",
"decompound_mode": "mixed",
"discard_punctuation": "false",
"user_dictionary": "userdict_ko.txt",
"lenient": "true"
}
},
"analyzer": {
"my_analyzer": {
"type": "custom",
"tokenizer": "nori_user_dict"
}
}
}
}
}
}
GET nori_sample/_analyze
{
"analyzer": "my_analyzer",
"text": "세종시" <1>
}
```
1. Sejong city
The above `analyze` request returns the following:
```console-result
{
"tokens" : [ {
"token" : "세종시",
"start_offset" : 0,
"end_offset" : 3,
"type" : "word",
"position" : 0,
"positionLength" : 2 <1>
}, {
"token" : "세종",
"start_offset" : 0,
"end_offset" : 2,
"type" : "word",
"position" : 0
}, {
"token" : "시",
"start_offset" : 2,
"end_offset" : 3,
"type" : "word",
"position" : 1
}]
}
```
1. This is a compound token that spans two positions (`mixed` mode).
`user_dictionary_rules`
: You can also inline the rules directly in the tokenizer definition using the `user_dictionary_rules` option:
```console
PUT nori_sample
{
"settings": {
"index": {
"analysis": {
"tokenizer": {
"nori_user_dict": {
"type": "nori_tokenizer",
"decompound_mode": "mixed",
"user_dictionary_rules": ["c++", "C쁠쁠", "세종", "세종시 세종 시"]
}
},
"analyzer": {
"my_analyzer": {
"type": "custom",
"tokenizer": "nori_user_dict"
}
}
}
}
}
}
```
The `nori_tokenizer` sets a number of additional attributes per token that are used by token filters to modify the stream. You can view all these additional attributes with the following request:
```console
GET _analyze
{
"tokenizer": "nori_tokenizer",
"text": "뿌리가 깊은 나무는", <1>
"attributes" : ["posType", "leftPOS", "rightPOS", "morphemes", "reading"],
"explain": true
}
```
1. A tree with deep roots
Which responds with:
```console-result
{
"detail": {
"custom_analyzer": true,
"charfilters": [],
"tokenizer": {
"name": "nori_tokenizer",
"tokens": [
{
"token": "뿌리",
"start_offset": 0,
"end_offset": 2,
"type": "word",
"position": 0,
"leftPOS": "NNG(General Noun)",
"morphemes": null,
"posType": "MORPHEME",
"reading": null,
"rightPOS": "NNG(General Noun)"
},
{
"token": "가",
"start_offset": 2,
"end_offset": 3,
"type": "word",
"position": 1,
"leftPOS": "JKS(Subject case marker)",
"morphemes": null,
"posType": "MORPHEME",
"reading": null,
"rightPOS": "JKS(Subject case marker)"
},
{
"token": "깊",
"start_offset": 4,
"end_offset": 5,
"type": "word",
"position": 2,
"leftPOS": "VA(Adjective)",
"morphemes": null,
"posType": "MORPHEME",
"reading": null,
"rightPOS": "VA(Adjective)"
},
{
"token": "은",
"start_offset": 5,
"end_offset": 6,
"type": "word",
"position": 3,
"leftPOS": "ETM(Adnominal form transformative ending)",
"morphemes": null,
"posType": "MORPHEME",
"reading": null,
"rightPOS": "ETM(Adnominal form transformative ending)"
},
{
"token": "나무",
"start_offset": 7,
"end_offset": 9,
"type": "word",
"position": 4,
"leftPOS": "NNG(General Noun)",
"morphemes": null,
"posType": "MORPHEME",
"reading": null,
"rightPOS": "NNG(General Noun)"
},
{
"token": "는",
"start_offset": 9,
"end_offset": 10,
"type": "word",
"position": 5,
"leftPOS": "JX(Auxiliary postpositional particle)",
"morphemes": null,
"posType": "MORPHEME",
"reading": null,
"rightPOS": "JX(Auxiliary postpositional particle)"
}
]
},
"tokenfilters": []
}
}
```