OpenSearch/docs/plugins/analysis-kuromoji.asciidoc

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[[analysis-kuromoji]]
=== Japanese (kuromoji) Analysis Plugin
The Japanese (kuromoji) Analysis plugin integrates Lucene kuromoji analysis
module into {es}.
:plugin_name: analysis-kuromoji
include::install_remove.asciidoc[]
[[analysis-kuromoji-analyzer]]
==== `kuromoji` analyzer
The `kuromoji` analyzer consists of the following tokenizer and token filters:
* <<analysis-kuromoji-tokenizer,`kuromoji_tokenizer`>>
* <<analysis-kuromoji-baseform,`kuromoji_baseform`>> token filter
* <<analysis-kuromoji-speech,`kuromoji_part_of_speech`>> token filter
* {ref}/analysis-cjk-width-tokenfilter.html[`cjk_width`] token filter
* <<analysis-kuromoji-stop,`ja_stop`>> token filter
* <<analysis-kuromoji-stemmer,`kuromoji_stemmer`>> token filter
* {ref}/analysis-lowercase-tokenfilter.html[`lowercase`] token filter
It supports the `mode` and `user_dictionary` settings from
<<analysis-kuromoji-tokenizer,`kuromoji_tokenizer`>>.
[discrete]
[[kuromoji-analyzer-normalize-full-width-characters]]
==== Normalize full-width characters
The `kuromoji_tokenizer` tokenizer uses characters from the MeCab-IPADIC
dictionary to split text into tokens. The dictionary includes some full-width
characters, such as `` and ``. If a text contains full-width characters,
the tokenizer can produce unexpected tokens.
For example, the `kuromoji_tokenizer` tokenizer converts the text
`  ` to the tokens `[ culture, o, f, japan ]`
instead of `[ culture, of, japan ]`.
To avoid this, add the <<analysis-icu-normalization-charfilter,`icu_normalizer`
character filter>> to a custom analyzer based on the `kuromoji` analyzer. The
`icu_normalizer` character filter converts full-width characters to their normal
equivalents.
First, duplicate the `kuromoji` analyzer to create the basis for a custom
analyzer. Then add the `icu_normalizer` character filter to the custom analyzer.
For example:
[source,console]
----
PUT index-00001
{
"settings": {
"index": {
"analysis": {
"analyzer": {
"kuromoji_normalize": { <1>
"char_filter": [
"icu_normalizer" <2>
],
"tokenizer": "kuromoji_tokenizer",
"filter": [
"kuromoji_baseform",
"kuromoji_part_of_speech",
"cjk_width",
"ja_stop",
"kuromoji_stemmer",
"lowercase"
]
}
}
}
}
}
}
----
<1> Creates a new custom analyzer, `kuromoji_normalize`, based on the `kuromoji`
analyzer.
<2> Adds the `icu_normalizer` character filter to the analyzer.
[[analysis-kuromoji-charfilter]]
==== `kuromoji_iteration_mark` character filter
The `kuromoji_iteration_mark` normalizes Japanese horizontal iteration marks
(_odoriji_) to their expanded form. It accepts the following settings:
`normalize_kanji`::
Indicates whether kanji iteration marks should be normalize. Defaults to `true`.
`normalize_kana`::
Indicates whether kana iteration marks should be normalized. Defaults to `true`
[[analysis-kuromoji-tokenizer]]
==== `kuromoji_tokenizer`
The `kuromoji_tokenizer` accepts the following settings:
`mode`::
+
--
The tokenization mode determines how the tokenizer handles compound and
unknown words. It can be set to:
`normal`::
Normal segmentation, no decomposition for compounds. Example output:
関西国際空港
アブラカダブラ
`search`::
Segmentation geared towards search. This includes a decompounding process
for long nouns, also including the full compound token as a synonym.
Example output:
関西, 関西国際空港, 国際, 空港
アブラカダブラ
`extended`::
Extended mode outputs unigrams for unknown words. Example output:
関西, 関西国際空港, 国際, 空港
ア, ブ, ラ, カ, ダ, ブ, ラ
--
`discard_punctuation`::
Whether punctuation should be discarded from the output. Defaults to `true`.
`user_dictionary`::
+
--
The Kuromoji tokenizer uses the MeCab-IPADIC dictionary by default. A `user_dictionary`
may be appended to the default dictionary. The dictionary should have the following CSV format:
[source,csv]
-----------------------
<text>,<token 1> ... <token n>,<reading 1> ... <reading n>,<part-of-speech tag>
-----------------------
--
As a demonstration of how the user dictionary can be used, save the following
dictionary to `$ES_HOME/config/userdict_ja.txt`:
[source,csv]
-----------------------
東京スカイツリー,東京 スカイツリー,トウキョウ スカイツリー,カスタム名詞
-----------------------
--
You can also inline the rules directly in the tokenizer definition using
the `user_dictionary_rules` option:
[source,console]
--------------------------------------------------
PUT nori_sample
{
"settings": {
"index": {
"analysis": {
"tokenizer": {
"kuromoji_user_dict": {
"type": "kuromoji_tokenizer",
"mode": "extended",
"user_dictionary_rules": ["東京スカイツリー,東京 スカイツリー,トウキョウ スカイツリー,カスタム名詞"]
}
},
"analyzer": {
"my_analyzer": {
"type": "custom",
"tokenizer": "kuromoji_user_dict"
}
}
}
}
}
}
--------------------------------------------------
--
`nbest_cost`/`nbest_examples`::
+
--
Additional expert user parameters `nbest_cost` and `nbest_examples` can be used
to include additional tokens that most likely according to the statistical model.
If both parameters are used, the largest number of both is applied.
`nbest_cost`::
The `nbest_cost` parameter specifies an additional Viterbi cost.
The KuromojiTokenizer will include all tokens in Viterbi paths that are
within the nbest_cost value of the best path.
`nbest_examples`::
The `nbest_examples` can be used to find a `nbest_cost` value based on examples.
For example, a value of /箱根山-箱根/成田空港-成田/ indicates that in the texts,
箱根山 (Mt. Hakone) and 成田空港 (Narita Airport) we'd like a cost that gives is us
箱根 (Hakone) and 成田 (Narita).
--
Then create an analyzer as follows:
[source,console]
--------------------------------------------------
PUT kuromoji_sample
{
"settings": {
"index": {
"analysis": {
"tokenizer": {
"kuromoji_user_dict": {
"type": "kuromoji_tokenizer",
"mode": "extended",
"discard_punctuation": "false",
"user_dictionary": "userdict_ja.txt"
}
},
"analyzer": {
"my_analyzer": {
"type": "custom",
"tokenizer": "kuromoji_user_dict"
}
}
}
}
}
}
GET kuromoji_sample/_analyze
{
"analyzer": "my_analyzer",
"text": "東京スカイツリー"
}
--------------------------------------------------
The above `analyze` request returns the following:
[source,console-result]
--------------------------------------------------
{
"tokens" : [ {
"token" : "東京",
"start_offset" : 0,
"end_offset" : 2,
"type" : "word",
"position" : 0
}, {
"token" : "スカイツリー",
"start_offset" : 2,
"end_offset" : 8,
"type" : "word",
"position" : 1
} ]
}
--------------------------------------------------
`discard_compound_token`::
Whether original compound tokens should be discarded from the output with `search` mode. Defaults to `false`.
Example output with `search` or `extended` mode and this option `true`:
関西, 国際, 空港
NOTE: If a text contains full-width characters, the `kuromoji_tokenizer`
tokenizer can produce unexpected tokens. To avoid this, add the
<<analysis-icu-normalization-charfilter,`icu_normalizer` character filter>> to
your analyzer. See <<kuromoji-analyzer-normalize-full-width-characters>>.
[[analysis-kuromoji-baseform]]
==== `kuromoji_baseform` token filter
The `kuromoji_baseform` token filter replaces terms with their
BaseFormAttribute. This acts as a lemmatizer for verbs and adjectives. Example:
[source,console]
--------------------------------------------------
PUT kuromoji_sample
{
"settings": {
"index": {
"analysis": {
"analyzer": {
"my_analyzer": {
"tokenizer": "kuromoji_tokenizer",
"filter": [
"kuromoji_baseform"
]
}
}
}
}
}
}
GET kuromoji_sample/_analyze
{
"analyzer": "my_analyzer",
"text": "飲み"
}
--------------------------------------------------
which responds with:
[source,console-result]
--------------------------------------------------
{
"tokens" : [ {
"token" : "飲む",
"start_offset" : 0,
"end_offset" : 2,
"type" : "word",
"position" : 0
} ]
}
--------------------------------------------------
[[analysis-kuromoji-speech]]
==== `kuromoji_part_of_speech` token filter
The `kuromoji_part_of_speech` token filter removes tokens that match a set of
part-of-speech tags. It accepts the following setting:
`stoptags`::
An array of part-of-speech tags that should be removed. It defaults to the
`stoptags.txt` file embedded in the `lucene-analyzer-kuromoji.jar`.
For example:
[source,console]
--------------------------------------------------
PUT kuromoji_sample
{
"settings": {
"index": {
"analysis": {
"analyzer": {
"my_analyzer": {
"tokenizer": "kuromoji_tokenizer",
"filter": [
"my_posfilter"
]
}
},
"filter": {
"my_posfilter": {
"type": "kuromoji_part_of_speech",
"stoptags": [
"助詞-格助詞-一般",
"助詞-終助詞"
]
}
}
}
}
}
}
GET kuromoji_sample/_analyze
{
"analyzer": "my_analyzer",
"text": "寿司がおいしいね"
}
--------------------------------------------------
Which responds with:
[source,console-result]
--------------------------------------------------
{
"tokens" : [ {
"token" : "寿司",
"start_offset" : 0,
"end_offset" : 2,
"type" : "word",
"position" : 0
}, {
"token" : "おいしい",
"start_offset" : 3,
"end_offset" : 7,
"type" : "word",
"position" : 2
} ]
}
--------------------------------------------------
[[analysis-kuromoji-readingform]]
==== `kuromoji_readingform` token filter
The `kuromoji_readingform` token filter replaces the token with its reading
form in either katakana or romaji. It accepts the following setting:
`use_romaji`::
Whether romaji reading form should be output instead of katakana. Defaults to `false`.
When using the pre-defined `kuromoji_readingform` filter, `use_romaji` is set
to `true`. The default when defining a custom `kuromoji_readingform`, however,
is `false`. The only reason to use the custom form is if you need the
katakana reading form:
[source,console]
--------------------------------------------------
PUT kuromoji_sample
{
"settings": {
"index": {
"analysis": {
"analyzer": {
"romaji_analyzer": {
"tokenizer": "kuromoji_tokenizer",
"filter": [ "romaji_readingform" ]
},
"katakana_analyzer": {
"tokenizer": "kuromoji_tokenizer",
"filter": [ "katakana_readingform" ]
}
},
"filter": {
"romaji_readingform": {
"type": "kuromoji_readingform",
"use_romaji": true
},
"katakana_readingform": {
"type": "kuromoji_readingform",
"use_romaji": false
}
}
}
}
}
}
GET kuromoji_sample/_analyze
{
"analyzer": "katakana_analyzer",
"text": "寿司" <1>
}
GET kuromoji_sample/_analyze
{
"analyzer": "romaji_analyzer",
"text": "寿司" <2>
}
--------------------------------------------------
<1> Returns `スシ`.
<2> Returns `sushi`.
[[analysis-kuromoji-stemmer]]
==== `kuromoji_stemmer` token filter
The `kuromoji_stemmer` token filter normalizes common katakana spelling
variations ending in a long sound character by removing this character
(U+30FC). Only full-width katakana characters are supported.
This token filter accepts the following setting:
`minimum_length`::
Katakana words shorter than the `minimum length` are not stemmed (default
is `4`).
[source,console]
--------------------------------------------------
PUT kuromoji_sample
{
"settings": {
"index": {
"analysis": {
"analyzer": {
"my_analyzer": {
"tokenizer": "kuromoji_tokenizer",
"filter": [
"my_katakana_stemmer"
]
}
},
"filter": {
"my_katakana_stemmer": {
"type": "kuromoji_stemmer",
"minimum_length": 4
}
}
}
}
}
}
GET kuromoji_sample/_analyze
{
"analyzer": "my_analyzer",
"text": "コピー" <1>
}
GET kuromoji_sample/_analyze
{
"analyzer": "my_analyzer",
"text": "サーバー" <2>
}
--------------------------------------------------
<1> Returns `コピー`.
<2> Return `サーバ`.
[[analysis-kuromoji-stop]]
==== `ja_stop` token filter
The `ja_stop` token filter filters out Japanese stopwords (`_japanese_`), and
any other custom stopwords specified by the user. This filter only supports
the predefined `_japanese_` stopwords list. If you want to use a different
predefined list, then use the
{ref}/analysis-stop-tokenfilter.html[`stop` token filter] instead.
[source,console]
--------------------------------------------------
PUT kuromoji_sample
{
"settings": {
"index": {
"analysis": {
"analyzer": {
"analyzer_with_ja_stop": {
"tokenizer": "kuromoji_tokenizer",
"filter": [
"ja_stop"
]
}
},
"filter": {
"ja_stop": {
"type": "ja_stop",
"stopwords": [
"_japanese_",
"ストップ"
]
}
}
}
}
}
}
GET kuromoji_sample/_analyze
{
"analyzer": "analyzer_with_ja_stop",
"text": "ストップは消える"
}
--------------------------------------------------
The above request returns:
[source,console-result]
--------------------------------------------------
{
"tokens" : [ {
"token" : "消える",
"start_offset" : 5,
"end_offset" : 8,
"type" : "word",
"position" : 2
} ]
}
--------------------------------------------------
[[analysis-kuromoji-number]]
==== `kuromoji_number` token filter
The `kuromoji_number` token filter normalizes Japanese numbers (kansūji)
to regular Arabic decimal numbers in half-width characters. For example:
[source,console]
--------------------------------------------------
PUT kuromoji_sample
{
"settings": {
"index": {
"analysis": {
"analyzer": {
"my_analyzer": {
"tokenizer": "kuromoji_tokenizer",
"filter": [
"kuromoji_number"
]
}
}
}
}
}
}
GET kuromoji_sample/_analyze
{
"analyzer": "my_analyzer",
"text": "一〇〇〇"
}
--------------------------------------------------
Which results in:
[source,console-result]
--------------------------------------------------
{
"tokens" : [ {
"token" : "1000",
"start_offset" : 0,
"end_offset" : 4,
"type" : "word",
"position" : 0
} ]
}
--------------------------------------------------