Lindera

A morphological analysis library in Rust. This project fork from kuromoji-rs.

Lindera aims to build a library which is easy to install and provides concise APIs for various Rust applications.

The following products are required to build:

Rust >= 1.46.0

Tokenizer Usage

Basic example

Put the following in Cargo.toml:

[dependencies]
lindera-tokenizer = { version = "0.24.0", features = ["ipadic"] }

This example covers the basic usage of Lindera.

It will:

Create a tokenizer in normal mode
Tokenize the input text
Output the tokens

use lindera_core::{mode::Mode, LinderaResult};
use lindera_dictionary::{DictionaryConfig, DictionaryKind};
use lindera_tokenizer::tokenizer::{Tokenizer, TokenizerConfig};

fn main() -> LinderaResult<()> {
    let dictionary = DictionaryConfig {
        kind: Some(DictionaryKind::IPADIC),
        path: None,
    };

    let config = TokenizerConfig {
        dictionary,
        user_dictionary: None,
        mode: Mode::Normal,
    };

    // create tokenizer
    let tokenizer = Tokenizer::from_config(config)?;

    // tokenize the text
    let tokens = tokenizer.tokenize("関西国際空港限定トートバッグ")?;

    // output the tokens
    for token in tokens {
        println!("{}", token.text);
    }

    Ok(())
}

The above example can be run as follows:

% cargo run --features=ipadic --example=ipadic_basic_example

You can see the result as follows:

関西国際空港
限定
トートバッグ

User dictionary example

You can give user dictionary entries along with the default system dictionary. User dictionary should be a CSV with following format.

<surface>,<part_of_speech>,<reading>

For example:

% cat ./resources/simple_userdic.csv
東京スカイツリー,カスタム名詞,トウキョウスカイツリー
東武スカイツリーライン,カスタム名詞,トウブスカイツリーライン
とうきょうスカイツリー駅,カスタム名詞,トウキョウスカイツリーエキ

With an user dictionary, Tokenizer will be created as follows:

use std::path::PathBuf;

use lindera_tokenizer::tokenizer::{Tokenizer, TokenizerConfig};
use lindera_core::viterbi::Mode;
use lindera_core::LinderaResult;

fn main() -> LinderaResult<()> {
    let dictionary = DictionaryConfig {
        kind: Some(DictionaryKind::IPADIC),
        path: None,
    };

    let user_dictionary = Some(UserDictionaryConfig {
        kind: DictionaryKind::IPADIC,
        path: PathBuf::from("./resources/ipadic_simple_userdic.csv"),
    });

    let config = TokenizerConfig {
        dictionary,
        user_dictionary,
        mode: Mode::Normal,
    };

    let tokenizer = Tokenizer::from_config(config)?;

    // tokenize the text
    let tokens = tokenizer.tokenize("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")?;

    // output the tokens
    for token in tokens {
        println!("{}", token.text);
    }

    Ok(())
}

The above example can be by cargo run --example:

% cargo run --features=ipadic --example=ipadic_userdic_example
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

Anzalyzer Usage

Basic example

Put the following in Cargo.toml:

[dependencies]
lindera-analyzer = { version = "0.24.0", features = ["ipadic", "filter"] }

This example covers the basic usage of Lindera Analysis Framework.

It will:

Apply character filter for Unicode normalization (NFKC)
Tokenize the input text with IPADIC
Apply token filters for removing stop tags (Part-of-speech) and Japanese Katakana stem filter

use std::{fs, path::PathBuf};

use lindera_analyzer::analyzer::Analyzer;
use lindera_core::LinderaResult;

fn main() -> LinderaResult<()> {
    let path = PathBuf::from(env!("CARGO_MANIFEST_DIR"))
        .join("../resources")
        .join("lindera_ipadic_conf.json");

    let config_bytes = fs::read(path).unwrap();

    let analyzer = Analyzer::from_slice(&config_bytes).unwrap();

    let mut text = "Ｌｉｎｄｅｒａは形態素解析ｴﾝｼﾞﾝです。ユーザー辞書も利用可能です。".to_string();
    println!("text: {}", text);

    // tokenize the text
    let tokens = analyzer.analyze(&text)?;

    // output the tokens
    for token in tokens {
        println!(
            "token: {:?}, start: {:?}, end: {:?}, details: {:?}",
            token.text,
            token.byte_start,
            token.byte_end,
            token.details
        );
    }

    Ok(())
}

The above example can be run as follows:

% cargo run --features=ipadic,filter --example=analysis_example

You can see the result as follows:

text: Ｌｉｎｄｅｒａは形態素解析ｴﾝｼﾞﾝです。ユーザー辞書も利用可能です。
token: Lindera, start: 0, end: 21, details: Some(["UNK"])
token: 形態素, start: 24, end: 33, details: Some(["名詞", "一般", "*", "*", "*", "*", "形態素", "ケイタイソ", "ケイタイソ"])
token: 解析, start: 33, end: 39, details: Some(["名詞", "サ変接続", "*", "*", "*", "*", "解析", "カイセキ", "カイセキ"])
token: エンジン, start: 39, end: 54, details: Some(["名詞", "一般", "*", "*", "*", "*", "エンジン", "エンジン", "エンジン"])
token: ユーザ, start: 0, end: 26, details: Some(["名詞", "一般", "*", "*", "*", "*", "ユーザー", "ユーザー", "ユーザー"])
token: 辞書, start: 26, end: 32, details: Some(["名詞", "一般", "*", "*", "*", "*", "辞書", "ジショ", "ジショ"])
token: 利用, start: 35, end: 41, details: Some(["名詞", "サ変接続", "*", "*", "*", "*", "利用", "リヨウ", "リヨー"])
token: 可能, start: 41, end: 47, details: Some(["名詞", "形容動詞語幹", "*", "*", "*", "*", "可能", "カノウ", "カノー"])