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