ウズベキ語の形状に関するアノテートされた形態学的データセット: ルールベースの機械学習アプローチへ
Nilufar Abdurakhmonova1, Raima Shirinova1, Rano Sayfullayeva1
1National University of Uzbekistan named after Mirzo Ulugbek, 4, University str., Tashkent city 100174, Uzbekistan.
Data in brief
|August 27, 2025
まとめ
ウズベク語のための新しい形質学的に注釈されたデータセットが作成されました. このリソースは,テキスト生成と文法訂正を含む自然言語処理 (NLP) の研究を支援します.
科学分野:
- コンピュータ言語学
- 自然言語処理
- レキシコグラフィ
背景:
- ウズベク語のような morfologically豊かな言語のための注釈されたリソースの限られた可用性.
- ウズベキスタン語解析アルゴリズムを評価するための標準化されたデータセットの必要性.
- 下流NLPのタスクにおける形態学的情報の重要性
研究 の 目的:
- ウズベキスタン morfological分析のための新しい,手動で注釈されたデータセットを導入する.
- 異なるウズベキスタン語の形態学的分析技術を評価するための基準を提供すること.
- ウズベキスタンNLPの進歩を促進する.
主な方法:
- 3022の手動で注釈されたウズベキスタン語形のデータセットの作成.
- アノテーションには,ルート,アフィックス,およびスピーチの部分情報が含まれています.
- ルールベースのステミングアルゴリズムと条件付きランダムフィールド (CRF) モデルの実装と比較.
主要な成果:
- ウズベキスタンの形態学データセットの作成と公開に成功しました.
- ウズベキスタンの形態学分析のためのルールベースのアプローチと機械学習のアプローチの比較分析.
- ジェンダーのテストは 法律,政治経済,教育文献で一般化されることが示されました
結論:
- アノテーションされたデータセットは,ウズベキスタンのNLP研究のための基本的なリソースとして機能します.
- この研究は,ウズベキスタンの異なる形態学的分析方法の有効性についての洞察を提供します.
- テキスト生成や文法訂正などのアプリケーションで このデータセットを活用できます
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