Lindera CLI

A morphological analysis command-line interface for Lindera.

Install

You can install binary via cargo as follows:

% cargo install lindera-cli

Alternatively, you can download a binary from the following release page:

• https://github.com/lindera-morphology/lindera/releases

Build

The following products are required to build:

• Rust >= 1.46.0

% cargo build --release

Build with IPADIC (Japanese dictionary)

The "ipadic" feature flag allows Lindera to include IPADIC.

% cargo build --release --features=ipadic

Build with UniDic (Japanese dictionary)

The "unidic" feature flag allows Lindera to include UniDic.

% cargo build --release --features=unidic

Build with ko-dic (Korean dictionary)

The "ko-dic" feature flag allows Lindera to include ko-dic.

% cargo build --release --features=ko-dic

Build with CC-CEDICT (Chinese dictionary)

The "cc-cedict" feature flag allows Lindera to include CC-CEDICT.

% cargo build --release --features=cc-cedict

Build small binary

You can reduce the size of the binary containing the lindera by using the "compress" feature flag.
Instead, you will be penalized for the execution time of the program.

% cargo build --release --features=compress

Build dictionary

IPADIC (Japanese dictionary)

% curl -L -o /tmp/mecab-ipadic-2.7.0-20070801.tar.gz "https://github.com/lindera-morphology/mecab-ipadic/archive/refs/tags/2.7.0-20070801.tar.gz"
% tar zxvf /tmp/mecab-ipadic-2.7.0-20070801.tar.gz -C /tmp
% lindera build --dictionary-kind=ipadic /tmp/mecab-ipadic-2.7.0-20070801 /tmp/lindera-ipadic-2.7.0-20070801
% ls -al /tmp/lindera-ipadic-2.7.0-20070801

CC-CEDICT (Chinese dictionary)

% curl -L -o /tmp/CC-CEDICT-MeCab-0.1.0-20200409.tar.gz "https://github.com/lindera-morphology/CC-CEDICT-MeCab/archive/refs/tags/0.1.0-20200409.tar.gz"
% tar zxvf /tmp/CC-CEDICT-MeCab-0.1.0-20200409.tar.gz -C /tmp
% lindera build --dictionary-kind=cc-cedict /tmp/CC-CEDICT-MeCab-0.1.0-20200409 /tmp/lindera-cc-cedict-0.1.0-20200409
% ls -al /tmp/lindera-cc-cedict-0.1.0-20200409

ko-dic (Korean dictionary)

% curl -L -o /tmp/mecab-ko-dic-2.1.1-20180720.tar.gz "https://github.com/lindera-morphology/mecab-ko-dic/archive/refs/tags/2.1.1-20180720.tar.gz"
% tar zxvf /tmp/mecab-ko-dic-2.1.1-20180720.tar.gz -C /tmp
% lindera build --dictionary-kind=ko-dic /tmp/mecab-ko-dic-2.1.1-20180720 /tmp/lindera-ko-dic-2.1.1-20180720
% ls -al /tmp/lindera-ko-dic-2.1.1-20180720

UniDic (Japanese dictionary)

% curl -L -o /tmp/unidic-mecab-2.1.2.tar.gz "https://github.com/lindera-morphology/unidic-mecab/archive/refs/tags/2.1.2.tar.gz"
% tar zxvf /tmp/unidic-mecab-2.1.2.tar.gz -C /tmp
% lindera build --dictionary-kind=unidic /tmp/unidic-mecab-2.1.2 /tmp/lindera-unidic-2.1.2
% ls -al /tmp/lindera-unidic-2.1.2

Build user dictionary

Build IPADIC (Japanese dictionary)

For more details about user dictionary format please refer to the following URL:

• Lindera IPADIC Builder/User Dictionary Format

% lindera build --build-user-dictionary --dictionary-kind=ipadic ./resources/ipadic_simple_userdic.csv ./resources

Build CC-CEDICT (Chinese dictionary)

For more details about user dictionary format please refer to the following URL:

• Lindera CC-CEDICT Builder/User Dictionary Format

% lindera build --build-user-dictionary --dictionary-kind=cc-cedict ./resources/cc-cedict_simple_userdic.csv ./resources

Build ko-dic (Korean dictionary)

For more details about user dictionary format please refer to the following URL:

• Lindera ko-dic Builder/User Dictionary Format

% lindera build --build-user-dictionary --dictionary-kind=ko-dic ./resources/ko-dic_simple_userdic.csv ./resources

Build UniDic (Japanese dictionary)

For more details about user dictionary format please refer to the following URL:

• Lindera UniDic Builder/User Dictionary Format

% lindera build --build-user-dictionary --dictionary-kind=unidic ./resources/unidic_simple_userdic.csv ./resources

Tokenization

External dictionary

For example, text can be tokenized using a prepared dictionary as follows:

Tokenize with IPADIC (Japanese dictionary)

% echo "日本語の形態素解析を行うことができます。" | lindera tokenize --dictionary-path=/tmp/lindera-ipadic-2.7.0-20070801

日本語  名詞,一般,*,*,*,*,日本語,ニホンゴ,ニホンゴ
の      助詞,連体化,*,*,*,*,の,ノ,ノ
形態素  名詞,一般,*,*,*,*,形態素,ケイタイソ,ケイタイソ
解析    名詞,サ変接続,*,*,*,*,解析,カイセキ,カイセキ
を      助詞,格助詞,一般,*,*,*,を,ヲ,ヲ
行う    動詞,自立,*,*,五段・ワ行促音便,基本形,行う,オコナウ,オコナウ
こと    名詞,非自立,一般,*,*,*,こと,コト,コト
が      助詞,格助詞,一般,*,*,*,が,ガ,ガ
でき    動詞,自立,*,*,一段,連用形,できる,デキ,デキ
ます    助動詞,*,*,*,特殊・マス,基本形,ます,マス,マス
。      記号,句点,*,*,*,*,。,。,。
EOS

Tokenize with UniDic (Japanese dictionary)

% echo "日本語の形態素解析を行うことができます。" | lindera tokenize --dictionary-path=/tmp/lindera-unidic-2.1.2

日本語  名詞,一般,*,*,*,*,日本語,ニホンゴ,ニホンゴ
の      助詞,連体化,*,*,*,*,の,ノ,ノ
形態素  名詞,一般,*,*,*,*,形態素,ケイタイソ,ケイタイソ
解析    名詞,サ変接続,*,*,*,*,解析,カイセキ,カイセキ
を      助詞,格助詞,一般,*,*,*,を,ヲ,ヲ
行う    動詞,自立,*,*,五段・ワ行促音便,基本形,行う,オコナウ,オコナウ
こと    名詞,非自立,一般,*,*,*,こと,コト,コト
が      助詞,格助詞,一般,*,*,*,が,ガ,ガ
でき    動詞,自立,*,*,一段,連用形,できる,デキ,デキ
ます    助動詞,*,*,*,特殊・マス,基本形,ます,マス,マス
。      記号,句点,*,*,*,*,。,。,。
EOS

Tokenize ko-dic (Korean dictionary)

% echo "한국어의형태해석을실시할수있습니다." | lindera tokenize --dictionary-path=/tmp/lindera-ko-dic-2.1.1-20180720

한국어  NNG,*,F,한국어,Compound,*,*,한국/NNG/*+어/NNG/*
의      JKG,*,F,의,*,*,*,*
형태    NNG,*,F,형태,*,*,*,*
해석    NNG,행위,T,해석,*,*,*,*
을      JKO,*,T,을,*,*,*,*
실시    NNG,행위,F,실시,*,*,*,*
할      VV+ETM,*,T,할,Inflect,VV,ETM,하/VV/*+ᆯ/ETM/*
수      NNG,*,F,수,*,*,*,*
있      VX,*,T,있,*,*,*,*
습니다  EF,*,F,습니다,*,*,*,*
.       UNK
EOS

Tokenize with CC-CEDICT (Chinese dictionary)

% echo "可以进行中文形态学分析。" | lindera tokenize --dictionary-path=/tmp/lindera-cc-cedict-0.1.0-20200409

可以    *,*,*,*,ke3 yi3,可以,可以,can/may/possible/able to/not bad/pretty good/
进行    *,*,*,*,jin4 xing2,進行,进行,to advance/to conduct/underway/in progress/to do/to carry out/to carry on/to execute/
中文    *,*,*,*,Zhong1 wen2,中文,中文,Chinese language/
形态学  *,*,*,*,xing2 tai4 xue2,形態學,形态学,morphology (in biology or linguistics)/
分析    *,*,*,*,fen1 xi1,分析,分析,to analyze/analysis/CL:個|个[ge4]/
。      UNK
EOS

Self-contained dictionary

If you had a built-in IPADIC, it is also possible to switch to the self-contained dictionary and tokenize.

Tokenize with self-contained IPADIC (Japanese dictionary)

The following example uses the self-contained IPADIC to tokenize:

% echo "日本語の形態素解析を行うことができます。" | lindera tokenize --dictionary-kind=ipadic

日本語  名詞,一般,*,*,*,*,日本語,ニホンゴ,ニホンゴ
の      助詞,連体化,*,*,*,*,の,ノ,ノ
形態素  名詞,一般,*,*,*,*,形態素,ケイタイソ,ケイタイソ
解析    名詞,サ変接続,*,*,*,*,解析,カイセキ,カイセキ
を      助詞,格助詞,一般,*,*,*,を,ヲ,ヲ
行う    動詞,自立,*,*,五段・ワ行促音便,基本形,行う,オコナウ,オコナウ
こと    名詞,非自立,一般,*,*,*,こと,コト,コト
が      助詞,格助詞,一般,*,*,*,が,ガ,ガ
でき    動詞,自立,*,*,一段,連用形,できる,デキ,デキ
ます    助動詞,*,*,*,特殊・マス,基本形,ます,マス,マス
。      記号,句点,*,*,*,*,。,。,。
EOS

NOTE: To include IPADIC dictionary in the binary, you must build with the --features=ipadic option.

Tokenize with self-contained UniDic (Japanese dictionary)

If UniDic were built in, it could also be tokenized by switching to a self-contained dictionary in the same way:

% echo "日本語の形態素解析を行うことができます。" | lindera tokenize --dictionary-kind=unidic

日本    名詞,固有名詞,地名,国,*,*,ニッポン,日本,日本,ニッポン,日本,ニッポン,固,*,*,*,*
語      名詞,普通名詞,一般,*,*,*,ゴ,語,語,ゴ,語,ゴ,漢,*,*,*,*
の      助詞,格助詞,*,*,*,*,ノ,の,の,ノ,の,ノ,和,*,*,*,*
形態    名詞,普通名詞,一般,*,*,*,ケイタイ,形態,形態,ケータイ,形態,ケータイ,漢,*,*,*,*
素      接尾辞,名詞的,一般,*,*,*,ソ,素,素,ソ,素,ソ,漢,*,*,*,*
解析    名詞,普通名詞,サ変可能,*,*,*,カイセキ,解析,解析,カイセキ,解析,カイセキ,漢,*,*,*,*
を      助詞,格助詞,*,*,*,*,ヲ,を,を,オ,を,オ,和,*,*,*,*
行う    動詞,一般,*,*,五段-ワア行,連体形-一般,オコナウ,行う,行う,オコナウ,行う,オコナウ,和,*,*,*,*
こと    名詞,普通名詞,一般,*,*,*,コト,事,こと,コト,こと,コト,和,コ濁,基本形,*,*
が      助詞,格助詞,*,*,*,*,ガ,が,が,ガ,が,ガ,和,*,*,*,*
でき    動詞,非自立可能,*,*,上一段-カ行,連用形-一般,デキル,出来る,でき,デキ,できる,デキル,和,*,*,*,*
ます    助動詞,*,*,*,助動詞-マス,終止形-一般,マス,ます,ます,マス,ます,マス,和,*,*,*,*
。      補助記号,句点,*,*,*,*,,。,。,,。,,記号,*,*,*,*
EOS

NOTE: To include UniDic dictionary in the binary, you must build with the --features=unidic option.

Tokenize with self-contained ko-dic (Korean dictionary)

If ko-dic were built in, it could also be tokenized by switching to a self-contained dictionary in the same way:

% echo "한국어의형태해석을실시할수있습니다." | lindera tokenize --dictionary-kind=ko-dic

한국어  NNG,*,F,한국어,Compound,*,*,한국/NNG/*+어/NNG/*
의      JKG,*,F,의,*,*,*,*
형태    NNG,*,F,형태,*,*,*,*
해석    NNG,행위,T,해석,*,*,*,*
을      JKO,*,T,을,*,*,*,*
실시    NNG,행위,F,실시,*,*,*,*
할      VV+ETM,*,T,할,Inflect,VV,ETM,하/VV/*+ᆯ/ETM/*
수      NNG,*,F,수,*,*,*,*
있      VX,*,T,있,*,*,*,*
습니다  EF,*,F,습니다,*,*,*,*
.       UNK
EOS

NOTE: To include ko-dic dictionary in the binary, you must build with the --features=ko-dic option.

Tokenize with self-contained CC-CEDICT (Chinese dictionary)

If CC-CEDICT were built in, it could also be tokenized by switching to a self-contained dictionary in the same way:

% echo "可以进行中文形态学分析。" | lindera tokenize --dictionary-kind=cc-cedict

可以    *,*,*,*,ke3 yi3,可以,可以,can/may/possible/able to/not bad/pretty good/
进行    *,*,*,*,jin4 xing2,進行,进行,to advance/to conduct/underway/in progress/to do/to carry out/to carry on/to execute/
中文    *,*,*,*,Zhong1 wen2,中文,中文,Chinese language/
形态学  *,*,*,*,xing2 tai4 xue2,形態學,形态学,morphology (in biology or linguistics)/
分析    *,*,*,*,fen1 xi1,分析,分析,to analyze/analysis/CL:個|个[ge4]/
。      UNK
EOS

NOTE: To include CC-CEDICT dictionary in the binary, you must build with the --features=cc-cedict option.

User dictionary

Lindera supports two types of user dictionaries, one in CSV format and the other in binary format.

Use user dictionary (CSV format)

This will parse the given CSV file at runtime, build a dictionary, and then run the text tokenization.

% echo "東京スカイツリーの最寄り駅はとうきょうスカイツリー駅です" | lindera tokenize --dictionary-kind=ipadic --user-dictionary-path=./resources/simple_userdic.csv

東京スカイツリー        カスタム名詞,*,*,*,*,*,東京スカイツリー,トウキョウスカイツリー,*
の      助詞,連体化,*,*,*,*,の,ノ,ノ
最寄り駅        名詞,一般,*,*,*,*,最寄り駅,モヨリエキ,モヨリエキ
は      助詞,係助詞,*,*,*,*,は,ハ,ワ
とうきょうスカイツリー駅        カスタム名詞,*,*,*,*,*,とうきょうスカイツリー駅,トウキョウスカイツリーエキ,*
です    助動詞,*,*,*,特殊・デス,基本形,です,デス,デス
EOS

Use user dictionary (Binary format)

This will read the given pre-built user dictionary file and perform text tokenization. Please check the repository of each dictionary builder for the configuration of the user dictionary binary files.

% echo "東京スカイツリーの最寄り駅はとうきょうスカイツリー駅です" | lindera tokenize --dictionary-kind=ipadic --user-dictionary-path=./resources/ipadic_userdic.bin

東京スカイツリー        カスタム名詞,*,*,*,*,*,東京スカイツリー,トウキョウスカイツリー,*
の      助詞,連体化,*,*,*,*,の,ノ,ノ
最寄り駅        名詞,一般,*,*,*,*,最寄り駅,モヨリエキ,モヨリエキ
は      助詞,係助詞,*,*,*,*,は,ハ,ワ
とうきょうスカイツリー駅        カスタム名詞,*,*,*,*,*,とうきょうスカイツリー駅,トウキョウスカイツリーエキ,*
です    助動詞,*,*,*,特殊・デス,基本形,です,デス,デス
EOS

Tokenize mode

Lindera provides two tokenization modes: normal and decompose.

normal mode tokenizes faithfully based on words registered in the dictionary. (Default):

% echo "関西国際空港限定トートバッグ" | lindera tokenize --dictionary-kind=ipadic --mode=normal

関西国際空港    名詞,固有名詞,組織,*,*,*,関西国際空港,カンサイコクサイクウコウ,カンサイコクサイクーコー
限定    名詞,サ変接続,*,*,*,*,限定,ゲンテイ,ゲンテイ
トートバッグ    UNK,*,*,*,*,*,*,*,*
EOS

decompose mode tokenizes a compound noun words additionally:

% echo "関西国際空港限定トートバッグ" | lindera tokenize --dictionary-kind=ipadic --mode=decompose

関西    名詞,固有名詞,地域,一般,*,*,関西,カンサイ,カンサイ
国際    名詞,一般,*,*,*,*,国際,コクサイ,コクサイ
空港    名詞,一般,*,*,*,*,空港,クウコウ,クーコー
限定    名詞,サ変接続,*,*,*,*,限定,ゲンテイ,ゲンテイ
トートバッグ    UNK,*,*,*,*,*,*,*,*
EOS

Output format

Lindera provides three output formats: mecab, wakati and json.

mecab outputs results in a format like MeCab:

% echo "お待ちしております。" | lindera tokenize --dictionary-kind=ipadic --output-format=mecab

お待ち  名詞,サ変接続,*,*,*,*,お待ち,オマチ,オマチ
し  動詞,自立,*,*,サ変・スル,連用形,する,シ,シ
て  助詞,接続助詞,*,*,*,*,て,テ,テ
おり  動詞,非自立,*,*,五段・ラ行,連用形,おる,オリ,オリ
ます  助動詞,*,*,*,特殊・マス,基本形,ます,マス,マス
。  記号,句点,*,*,*,*,。,。,。
EOS

wakati outputs the token text separated by spaces:

% echo "お待ちしております。" | lindera tokenize --dictionary-kind=ipadic --output-format=wakati

お待ち し て おり ます 。

json outputs the token information in JSON format:

% echo "お待ちしております。" | lindera tokenize --dictionary-kind=ipadic --output-format=json

[
  {
    "text": "お待ち",
    "detail": [
      "名詞",
      "サ変接続",
      "*",
      "*",
      "*",
      "*",
      "お待ち",
      "オマチ",
      "オマチ"
    ]
  },
  {
    "text": "し",
    "detail": [
      "動詞",
      "自立",
      "*",
      "*",
      "サ変・スル",
      "連用形",
      "する",
      "シ",
      "シ"
    ]
  },
  {
    "text": "て",
    "detail": [
      "助詞",
      "接続助詞",
      "*",
      "*",
      "*",
      "*",
      "て",
      "テ",
      "テ"
    ]
  },
  {
    "text": "おり",
    "detail": [
      "動詞",
      "非自立",
      "*",
      "*",
      "五段・ラ行",
      "連用形",
      "おる",
      "オリ",
      "オリ"
    ]
  },
  {
    "text": "ます",
    "detail": [
      "助動詞",
      "*",
      "*",
      "*",
      "特殊・マス",
      "基本形",
      "ます",
      "マス",
      "マス"
    ]
  },
  {
    "text": "。",
    "detail": [
      "記号",
      "句点",
      "*",
      "*",
      "*",
      "*",
      "。",
      "。",
      "。"
    ]
  }
]

Filtering

Lindera introduced an analytical framework. Combine character filters, tokenizers, and token filters for more advanced text processing. Describe the character filter and token filter settings used for analysis in JSON.

% echo "すもももももももものうち" | lindera tokenize --dictionary-kind=ipadic --character-filter='unicode_normalize:{"kind":"nfkc"}' --token-filter='japanese_keep_tags:{"tags":["名詞,一般"]}'

すもも  名詞,一般,*,*,*,*,すもも,スモモ,スモモ
もも    名詞,一般,*,*,*,*,もも,モモ,モモ
もも    名詞,一般,*,*,*,*,もも,モモ,モモ
EOS

API reference

The API reference is available. Please see following URL:

• lindera-cli