# PyFCG: Fluid Construction Grammar in Python

arXiv: https://arxiv.org/abs/2505.12920 · HTML: https://mlsanity.com/paper/2505.12920/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 4 of its 26 references that are in the map.
- First posted on arXiv 19 May 2025.

## Builds on (most cited first, 4 of 4)

- [Stanza: A Python Natural Language Processing Toolkit for Many Human Languages](https://mlsanity.com/paper/2003.07082/) (2020)
- [The Better Your Syntax, the Better Your Semantics? Probing Pretrained Language Models for the English Comparative Correlative](https://mlsanity.com/paper/2210.13181/) (2022)
- [CxGBERT: BERT meets Construction Grammar](https://mlsanity.com/paper/2011.04134/) (2020)
- [UCxn: Typologically Informed Annotation of Constructions Atop Universal Dependencies](https://mlsanity.com/paper/2403.17748/) (2024)

## Built on by (most cited first, 1 of 1)

- [A Method for Learning Large-Scale Computational Construction Grammars from Semantically Annotated Corpora](https://mlsanity.com/paper/2603.12754/) (2026)

## Abstract (arXiv)

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.