# nvim_1Clause_1Line

**Repository Path**: llwwff/nvim_1Clause_1Line

## Basic Information

- **Project Name**: nvim_1Clause_1Line
- **Description**: 一行一个分句, 方便理解与抽取信息
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2023-05-02
- **Last Updated**: 2023-06-06

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

## why

To make long sentences, which may contain long clauses, easier to understand,
especially for Chinese people,
this plugin uses spaCy,
    a NLP lib written in python code, to split the text.
For a paragraph of long sentences,
the plugin will insert line break at punctuations and  stopwords,
which can be  configured,
to get only 1 clause per line.        

## setup

```
pip3 install spacy 
python3 -m spacy download en_core_web_sm
brew install apache-opennlp 
```

## usage


- use opennlp:   `opennlp SentenceDetector openNLP_en_sentence.bin 2>/dev/null < toy_article.txt`


## ref


https://github.com/lervag/vimtex/blob/1043b590d98fa3f069a0879c65293aa2c7c31b0d/doc/vimtex.txt#L728 

http://dustycloud.org/blog/vcs-friendly-patchable-document-line-wrapping 

https://github.com/sembr/specification


https://github.com/vim-autoformat/vim-autoformat

    https://github.com/cmhughes/latexindent.pl

    https://github.com/remarkjs/remark#example-checking-and-formatting-markdown-on-the-cli

vim with NLTK: 
    https://github.com/gmarmstrong/vim-muse


It's still very experimental, so use it at your own risk.

After installing just use `<M-p>` to format your text.
<!-- After installing just use `gq` to format your text. -->


## Basic NLP knowledge

https://spacy.io/api/token 

class Token : 
    An individual token — i.e. a word, punctuation symbol, whitespace, etc.

stop words:
     “stop signals” for the algorithm to process.
     e.g.: “a”, “and”, “the” and “of”.
     ref: https://www.nomidl.com/natural-language-processing/what-is-stop-word-in-nlp