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All Projects → taishi-i → Nagisa Tutorial Pycon2019

taishi-i / Nagisa Tutorial Pycon2019

Licence: mit
Code for PyCon JP 2019 talk "Python による日本語自然言語処理 〜系列ラベリングによる実世界テキスト分析〜"

Labels

jupyter-notebooknatural-language-processingnamed-entity-recognitionjapanese

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Python による日本語自然言語処理 〜系列ラベリングによる実世界テキスト分析〜

nagisa による単語分割と品詞タグ付けの実装方法

  1. 基本的な使い方: basic_usage.ipynb [Colab notebook]
  2. ワードクラウドの作成: word_cloud.ipynb [Colab notebook]

Python による固有表現抽出モデルの実装方法

  1. 事前準備: Speaker Deck
  2. 京都大学ウェブ文書リードコーパスの前処理: preprocess_kwdlc.py
  3. 固有表現抽出モデルの学習: train_kwdlc_model.py
  4. 学習済みモデルの利用方法: predict_kwdlc_model.py
  5. 固有表現ごとの正解率の確認: evaluate_kwdlc_model.py

参考リンク

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