languagetool-org/languagetool
Languagetool
LanguageTool is a multilingual grammar and style checking engine designed to detect spelling, grammar, and writing errors across multiple languages. It provides automated proofreading capabilities that can be deployed as a self-hosted server or executed as a standalone local desktop application.
The project distinguishes itself through a flexible rule development framework, allowing linguistic patterns to be defined via XML or implemented as custom Java classes. It utilizes n-gram frequency modeling for confused word detection and supports neural word embeddings to improve disambiguation between similar word pairs.
The engine covers a broad range of linguistic analysis capabilities, including part-of-speech tagging, sentence boundary definition, and markup-aware proofreading for documents containing HTML, XML, or LaTeX. It also features comprehensive dictionary management tools for compiling binary dictionaries and managing custom spell-checking rules.
Developers can integrate these capabilities into external applications using a REST-based API, which includes support for automatic language detection and access restriction controls.
Features
- Proofreading Tools - Ships a comprehensive suite of proofreading tools for detecting and correcting grammatical and stylistic errors in text.
- Spell and Grammar Checkers - Detects spelling, grammar, and style errors across multiple languages to improve overall writing quality.
- N-Gram Co-occurrence Models - Utilizes n-gram co-occurrence modeling to identify frequently confused words and rank spelling suggestions.
- Sentence Boundary Detection - Implements sentence boundary detection using regular expressions to split text into individual sentences for analysis.
- Text Error Detection APIs - Exposes a REST API for analyzing text and identifying grammar and style mistakes across multiple languages.
- Programmatic Proofreading Interfaces - Integrates automated text analysis and error detection into external applications via a REST API.
- Writing Error Detection - Analyzes text against collections of common misspellings and grammatical mistakes to identify writing errors.
- Spelling and Language Tools - Identifies misspelled words and manages custom dictionaries to ensure spelling accuracy across domains.
- Linguistic Rule Development - Provides advanced detection patterns using unification and specialized filters to target complex linguistic errors.
- Rule-Based Grammar Definitions - Defines linguistic patterns and error detection logic using XML schemas to match tokens and part-of-speech tags.
- Grammar Rule Specification - Allows creating custom grammar and style detection patterns using XML, regular expressions, and part-of-speech tags.
- Linguistic Token Matching - Analyzes text by breaking it into discrete tokens and applying unification and filter logic to detect errors.
- Character Offset Trackers - Uses character offset trackers to identify the exact positions of errors relative to the original raw text containing markup.
- Confused Word Detection - Uses large n-gram datasets to identify and correct frequently swapped words based on linguistic patterns.
- Language Detection Tools - Includes utilities for identifying the language of provided text content to apply the correct grammar rules.
- Text Analysis APIs - Provides a text analysis API to detect grammar and style errors based on provided language specifications.
- Linguistic Language Modules - Provides a framework for adding new languages by defining modules and writing custom error detection rules.
- Markup-Aware Analysis - Identifies errors in HTML, XML, or LaTeX documents by mapping text positions and ignoring tags.
- Spell Check Whitelisting - Allows marking specific words or patterns to be ignored by the spell checker in designated contexts.
- Spell Checking Rules - Provides mechanisms to define custom lists of ignored and prohibited words to refine spelling validation.
- Markup-Aware Text Analysis - Analyzes text in HTML, XML, or LaTeX by ignoring tags while maintaining character positions for accurate error highlighting.
- Linguistic Variable Capturing - Provides the ability to store matched text in variables for use in subsequent patterns and context-aware suggestions.
- Analysis Integration Interfaces - Provides programmatic interfaces for embedding grammar and style analysis tools into custom workflows and automated pipelines.
- Desktop Applications - Offers a standalone desktop application for local proofreading without requiring a remote server.
- Linguistic Extension Frameworks - Enables adding new languages via custom tagger dictionaries, disambiguators, and sentence segmentation rules.
- Proofreading Rule Specification - Implements specialized grammar and style checks using unification and tone tags to detect linguistic patterns.
- Self-Hosted Instances - Provides a local instance of the grammar checking engine to process text without relying on cloud services.
- Programmatic API Interfaces - Provides Java and HTTP interfaces that expose the full functionality of the proofreading engine for automation.
- Rule Logic Extensions - Allows implementation of complex validation logic by extending base Java classes for linguistic rules.
- Custom Dictionaries - Supports the use of user-defined word lists to improve and refine spell-checking accuracy.
- Regex-Based Exclusion Rules - Provides a system for specifying antipatterns or exclusion regexes to prevent conflicting rule triggers.
- Client-Server Architecture - Employs a client-server architecture where a central HTTP server handles the heavy lifting of text analysis.
- Java-Based Rule Implementation - Supports developing complex validation logic by extending base classes when XML patterns are insufficient.
- False Positive Filtering - Uses regex anti-patterns to prevent specific text sequences from triggering grammar or style rules.
- Suggestion Ranking - Integrates word usage frequency data to ensure the most common correct spellings appear first in suggestions.
- Rule Antipatterns - Prevents false positives by defining token sequences that deactivate specific matching rules.
- Proofreading Servers - Allows running a self-contained HTTP instance locally to process text without relying on external cloud services.
