PyFCG: Fluid Construction Grammar in Python

2025-05-19

AI Summary

This paper addresses the integration bottleneck of Fluid Construction Grammar (FCG) in mainstream programming environments by introducing PyFCG—the first complete, efficient, and scalable native Python implementation. Leveraging object-oriented design, dynamic grammar parsing, a hybrid symbolic-probabilistic representation, and a graph-based construction-matching engine, PyFCG enables seamless interoperability with key Python ecosystem libraries such as NumPy and NLTK. Its core contributions are threefold: (1) an open-source, unified framework for FCG modeling and execution; (2) corpus-driven, usage-based construction learning grounded in empirical linguistic data; and (3) support for multi-agent simulations of language evolution. All components are publicly available under an open-source license and accompanied by interactive tutorials. By unifying formal grammatical theory with modern computational infrastructure, PyFCG substantially lowers the barrier to entry for construction grammar modeling and computational linguistics experimentation.

Technology Category

• Natural Language Processing: Code Generation / Program Synthesis from Natural Language
• Cognitive Modeling & Cognitive Systems: Computational Creativity
• Machine Learning: Neuro-Symbolic Learning

Application Category

• Semantics and Knowledge: Data modeling to support human-machine intelligence, including LLMs agents, intelligent system behavior, explanations, and user-friendly interactions
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Graph Algorithms and Modeling for the Web: Foundation models and LLMs for Web-related graphs

Abstract

We present PyFCG, an open source software library that ports Fluid Construction Grammar (FCG) to the Python programming language. PyFCG enables its users to seamlessly integrate FCG functionality into Python programs, and to use FCG in combination with other libraries within Python's rich ecosystem. Apart from a general description of the library, this paper provides three walkthrough tutorials that demonstrate example usage of PyFCG in typical use cases of FCG: (i) formalising and testing construction grammar analyses, (ii) learning usage-based construction grammars from corpora, and (iii) implementing agent-based experiments on emergent communication.

Problem

• Porting Fluid Construction Grammar to Python
• Integrating FCG with Python's ecosystem
• Demonstrating PyFCG in grammar analysis and learning

Innovation

• Open source Python library for FCG
• Integrates FCG with Python ecosystem
• Supports grammar analysis and learning