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
. lenient
- Whether the
user_dictionary
should be deduplicated on the providedtext
. False by default causing duplicates to generate an error. 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:
<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
:
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:
PUT kuromoji_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
andnbest_examples
can be used to include additional tokens that are 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 anbest_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:
PUT kuromoji_sample
{
"settings": {
"index": {
"analysis": {
"tokenizer": {
"kuromoji_user_dict": {
"type": "kuromoji_tokenizer",
"mode": "extended",
"discard_punctuation": "false",
"user_dictionary": "userdict_ja.txt",
"lenient": "true"
}
},
"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:
{
"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 tofalse
. Example output withsearch
orextended
mode and this optiontrue
:関西, 国際, 空港
If a text contains full-width characters, the kuromoji_tokenizer
tokenizer can produce unexpected tokens. To avoid this, add the icu_normalizer
character filter to your analyzer. See Normalize full-width characters.