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@chax-at/simple-sentence-splitter

v0.2.3

Published

A sentence splitter, written for https://storywi.se, which works quite well

Downloads

84

Readme

@chax-npm/simple-sentence-splitter

Code

Find the code in the internal gitea and on github.

SentenceSplitter Package

Overview

The SentenceSplitter class is a sophisticated tool designed for splitting text input into individual sentences. It's particularly valuable for natural language processing (NLP) tasks that require sentence-level analysis.

Usage:

      import { SentenceSplitter } from '@chax-at/simple-sentence-splitter';
      const sentenceSplitter = new SentenceSplitter(text, language);
      // returns a promise
      return sentenceSplitter.process();

Key Features

  1. Text Preprocessing Accepts input string and language parameter Splits input into words Initializes data structures for tracking words, sentences, and overall sentence collection
  2. Language-Specific Handling Loads language-specific abbreviation data from JSON files Includes common abbreviations, regex patterns, and date formats Falls back to default values if language file is not found
  3. Sentence Boundary Detection Identifies sentence boundaries considering: Standard punctuation (periods, exclamation marks, question marks) Ellipsis (...) followed by capitalized words Numbers, Roman numerals, and date expressions Abbreviations to avoid false sentence breaks
  4. Abbreviation and Date Handling Implements methods to identify abbreviations and date expressions Prevents incorrect sentence splits in cases like "Mr. Smith" or "Oct. 21, 2023"
  5. Flexible Processing Iterates through each word, constructing sentences Splits sentences based on determined boundaries Handles cases where text doesn't end with typical sentence-ending punctuation Conclusion This package offers a robust solution for sentence splitting, adaptable to different languages and capable of handling various edge cases in text processing. It's an invaluable tool for applications in text analysis, machine translation, or any NLP task requiring sentence-level granularity.