OpenSearch/docs/plugins/analysis-kuromoji.asciidoc
Christoph Büscher 25aac4f77f
Remove include_type_name in asciidoc where possible (#37568)
The "include_type_name" parameter was temporarily introduced in #37285 to facilitate
moving the default parameter setting to "false" in many places in the documentation
code snippets. Most of the places can simply be reverted without causing errors.
In this change I looked for asciidoc files that contained the
"include_type_name=true" addition when creating new indices but didn't look
likey they made use of the "_doc" type for mappings. This is mostly the case
e.g. in the analysis docs where index creating often only contains settings. I
manually corrected the use of types in some places where the docs still used an
explicit type name and not the dummy "_doc" type.
2019-01-18 09:34:11 +01:00

537 lines
13 KiB
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[[analysis-kuromoji]]
=== Japanese (kuromoji) Analysis Plugin
The Japanese (kuromoji) Analysis plugin integrates Lucene kuromoji analysis
module into elasticsearch.
: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`>>.
[[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, 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
-----------------------
`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,js]
--------------------------------------------------
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"
}
--------------------------------------------------
// CONSOLE
The above `analyze` request returns the following:
[source,js]
--------------------------------------------------
{
"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
} ]
}
--------------------------------------------------
// TESTRESPONSE
[[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,js]
--------------------------------------------------
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"
}
--------------------------------------------------
// CONSOLE
which responds with:
[source,js]
--------------------------------------------------
{
"tokens" : [ {
"token" : "飲む",
"start_offset" : 0,
"end_offset" : 2,
"type" : "word",
"position" : 0
} ]
}
--------------------------------------------------
// TESTRESPONSE
[[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,js]
--------------------------------------------------
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"
}
--------------------------------------------------
// CONSOLE
Which responds with:
[source,js]
--------------------------------------------------
{
"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
} ]
}
--------------------------------------------------
// TESTRESPONSE
[[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,js]
--------------------------------------------------
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>
}
--------------------------------------------------
// CONSOLE
<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,js]
--------------------------------------------------
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>
}
--------------------------------------------------
// CONSOLE
<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,js]
--------------------------------------------------
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"
}
--------------------------------------------------
// CONSOLE
The above request returns:
[source,js]
--------------------------------------------------
{
"tokens" : [ {
"token" : "消える",
"start_offset" : 5,
"end_offset" : 8,
"type" : "word",
"position" : 2
} ]
}
--------------------------------------------------
// TESTRESPONSE
[[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,js]
--------------------------------------------------
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"
}
--------------------------------------------------
// CONSOLE
Which results in:
[source,js]
--------------------------------------------------
{
"tokens" : [ {
"token" : "1000",
"start_offset" : 0,
"end_offset" : 4,
"type" : "word",
"position" : 0
} ]
}
--------------------------------------------------
// TESTRESPONSE