lindera

Crates.iolindera
lib.rslindera
version0.36.0
sourcesrc
created_at2020-02-03 09:38:37.845567
updated_at2024-11-02 14:09:29.48413
descriptionA morphological analysis library.
homepagehttps://github.com/lindera-morphology/lindera
repositoryhttps://github.com/lindera-morphology/lindera
max_upload_size
id204417
size600,789
ikawaha (ikawaha)

documentation

https://docs.rs/lindera

README

Lindera

License: MIT Crates.io

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

Tokenization examples

Basic tokenization

Put the following in Cargo.toml:

[dependencies]
lindera = { version = "0.34.0", 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::dictionary::DictionaryKind;
use lindera::mode::Mode;
use lindera::tokenizer::{Tokenizer, TokenizerConfigBuilder};
use lindera::LinderaResult;

fn main() -> LinderaResult<()> {
    // Creates a new `TokenizerConfigBuilder` instance.
    // If the `LINDERA_CONFIG_PATH` environment variable is set, it will attempt to load the initial settings from the specified path.
    let mut config_builder = TokenizerConfigBuilder::new();
    config_builder.set_segmenter_dictionary_kind(&DictionaryKind::IPADIC);
    config_builder.set_segmenter_mode(&Mode::Normal);

    // Create the tokenizer.
    let tokenizer = Tokenizer::from_config(&config_builder.build())?;

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

    // Print the text and tokens.
    println!("text:\t{}", text);
    for token in tokens.iter_mut() {
        let details = token.details().join(",");
        println!("token:\t{}\t{}", token.text.as_ref(), details);
    }

    Ok(())
}

The above example can be run as follows:

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

You can see the result as follows:

text:   関西国際空港限定トートバッグ
token:  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
token:  限定    名詞,サ変接続,*,*,*,*,限定,ゲンテイ,ゲンテイ
token:  トートバッグ    UNK

Tokenization with user dictionary

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>

Put the following in Cargo.toml:

[dependencies]
lindera = { version = "0.34.0", features = ["ipadic"] }

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::dictionary::DictionaryKind;
use lindera::mode::Mode;
use lindera::tokenizer::{Tokenizer, TokenizerConfigBuilder};
use lindera::{dictionary, LinderaResult};

fn main() -> LinderaResult<()> {
    // Creates a new `TokenizerConfigBuilder` instance.
    // If the `LINDERA_CONFIG_PATH` environment variable is set, it will attempt to load the initial settings from the specified path.
    let mut config_builder = TokenizerConfigBuilder::new();
    config_builder.set_segmenter_dictionary_kind(&DictionaryKind::IPADIC);
    config_builder.set_segmenter_mode(&Mode::Normal);
    config_builder.set_segmenter_user_dictionary_path(
        PathBuf::from("./resources/ipadic_simple_userdic.csv").as_path(),
    );
    config_builder.set_segmenter_user_dictionary_kind(&DictionaryKind::IPADIC);

    // Create a tokenizer.
    let tokenizer = Tokenizer::from_config(&config_builder.build())?;

    // Tokenize a text.
    let text = "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";
    let mut tokens = tokenizer.tokenize(text)?;

    // Print the text and tokens.
    println!("text:\t{}", text);
    for token in tokens.iter_mut() {
        let details = token.details().join(",");
        println!("token:\t{}\t{}", token.text.as_ref(), details);
    }

    Ok(())
}

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

% cargo run --features=ipadic --example=tokenize_with_user_dict
text:   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
token:  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,*
token:  の      助詞,連体化,*,*,*,*,の,ノ,ノ
token:  最寄り駅        名詞,一般,*,*,*,*,最寄り駅,モヨリエキ,モヨリエキ
token:  は      助詞,係助詞,*,*,*,*,は,ハ,ワ
token:  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,*
token:  です    助動詞,*,*,*,特殊・デス,基本形,です,デス,デス

Tokenize with filters

Put the following in Cargo.toml:

[dependencies]
lindera = { version = "0.34.0", features = ["ipadic"] }

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::collections::HashSet;

use lindera::dictionary::DictionaryKind;
use lindera::mode::Mode;
use lindera::tokenizer::{Tokenizer, TokenizerConfigBuilder};

fn main() -> LinderaResult<()> {
    // Creates a new `TokenizerConfigBuilder` instance.
    // If the `LINDERA_CONFIG_PATH` environment variable is set, it will attempt to load the initial settings from the specified path.
    let mut config_builder = TokenizerConfigBuilder::new();
    config_builder.set_segmenter_dictionary_kind(&DictionaryKind::IPADIC);
    config_builder.set_segmenter_mode(&Mode::Normal);
    config_builder.append_character_filter("unicode_normalize", &json!({"kind": "nfkc"}));
    config_builder.append_character_filter(
        "japanese_iteration_mark",
        &json!({"normalize_kanji": true, "normalize_kana": true}),
    );
    config_builder.append_token_filter(
        "japanese_compound_word",
        &json!({
            "kind": "ipadic",
            "tags": [
                "名詞,数",
                "名詞,接尾,助数詞"
            ],
            "new_tag": "複合語"
        }),
    );
    config_builder.append_token_filter(
        "japanese_number",
        &json!({
            "tags": [
                "名詞,数"
            ]
        }),
    );
    config_builder.append_token_filter(
        "japanese_stop_tags",
        &json!({
            "tags": [
                "接続詞",
                "助詞",
                "助詞,格助詞",
                "助詞,格助詞,一般",
                "助詞,格助詞,引用",
                "助詞,格助詞,連語",
                "助詞,係助詞",
                "助詞,副助詞",
                "助詞,間投助詞",
                "助詞,並立助詞",
                "助詞,終助詞",
                "助詞,副助詞/並立助詞/終助詞",
                "助詞,連体化",
                "助詞,副詞化",
                "助詞,特殊",
                "助動詞",
                "記号",
                "記号,一般",
                "記号,読点",
                "記号,句点",
                "記号,空白",
                "記号,括弧閉",
                "その他,間投",
                "フィラー",
                "非言語音"
            ]
        }
    );

    // Create a tokenizer.
    let tokenizer = Tokenizer::from_config(&config_builder.build())?;_

    // Tokenize a text.
    let text = "Linderaは形態素解析エンジンです。ユーザー辞書も利用可能です。";
    let tokens = tokenizer.tokenize(text)?;

    // Print the text and tokens.
    println!("text: {}", text);
    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 --example=tokenize_with_filters

You can see the result as follows:

text: Linderaは形態素解析エンジンです。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: "ユーザー", start: 63, end: 75, details: Some(["名詞", "一般", "*", "*", "*", "*", "ユーザー", "ユーザー", "ユーザー"])
token: "辞書", start: 75, end: 81, details: Some(["名詞", "一般", "*", "*", "*", "*", "辞書", "ジショ", "ジショ"])
token: "利用", start: 84, end: 90, details: Some(["名詞", "サ変接続", "*", "*", "*", "*", "利用", "リヨウ", "リヨー"])
token: "可能", start: 90, end: 96, details: Some(["名詞", "形容動詞語幹", "*", "*", "*", "*", "可能", "カノウ", "カノー"])

API reference

The API reference is available. Please see following URL:

Commit count: 499

cargo fmt