EasyCCG

EasyCCG is a Combinatory Categorial Grammar (CCG) parser that implements all combinators and supports parsing to logical form. It provides a common grammar format and includes parameter estimation capabilities for probabilistic CCG models, making it suitable for natural language processing research and applications.

Key Features

• All Combinators — Implements the full set of CCG combinators for comprehensive grammatical coverage
• Logical Form Parsing — Converts parsed sentences into logical representations for semantic analysis
• Probabilistic Parameter Estimation — Supports training of probabilistic CCG models from data
• Common Grammar Format — Uses a standardized grammar format for interoperability
• N-best Parsing — Generates multiple parse candidates with ranking
• Boxer Integration — Produces Prolog output compatible with the Boxer semantic analysis system
• POS/NER Tag Support — Accepts pre-tagged input with part-of-speech and named entity recognition tags

Philosophy

EasyCCG is designed as a practical, efficient implementation of CCG parsing that balances theoretical completeness with computational performance, enabling both research experimentation and applied natural language processing tasks.