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https://github.com/ars-linguistica/pylfg

PyLFG is a Python library for working within the Lexical Functional Grammar (LFG) formalism. It provides a set of classes and methods for representing and manipulating LFG structures, including f-structures and c-structures.
https://github.com/ars-linguistica/pylfg

grammar grammar-parser lexical-functional-grammar python syntax-analysis

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PyLFG is a Python library for working within the Lexical Functional Grammar (LFG) formalism. It provides a set of classes and methods for representing and manipulating LFG structures, including f-structures and c-structures.

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README 

          
PyLFG - A Python package for parsing sentences using Lexical Functional Grammar (LFG)

=====================================================================================



.. image:: https://zenodo.org/badge/586289901.svg

   :target: https://zenodo.org/badge/latestdoi/586289901



Introduction

------------



PyLFG (Python Library for Lexical Functional Grammar) is a new

open-source project that aims to provide a comprehensive set of tools

for working within the Lexical Functional Grammar (LFG) formalism, developed by ARS Linguistica.

LFG is a syntactic theory that represents the structure of natural language

using a combination of lexical and functional information. This project

provides a set of classes and methods for representing and manipulating

LFG structures, including lexical functional structures (f-structures)

and c-structures.



PyLFG’s primary goal is to make LFG research more accessible to a wider

community by providing a fully modular library that allows researchers

to easily try new ideas and improve existing ones. The library will not

only parse sentences but also generate sentences from f-structures, and

it will have transfer capabilities to do automated translation.



PyLFG is also designed to be user-friendly, providing both a TUI

(Terminal User Interface) and a WebUI for easy interaction. The library

being written in Python makes it perfectly suited for linguistics

students who are taught Python in university.



The lack of open-source LFG parsers is a significant problem in the

field of linguistics research. Many academically developed LFG parsers

have been abandoned by their authors, making them inaccessible to the

wider community. This is a major obstacle for researchers who are

interested in studying LFG, as they are often forced to rely on

proprietary software that is difficult to access and modify.



The open-source nature of PyLFG is crucial in addressing this problem.

By providing an open-source LFG parser, PyLFG aims to make LFG research

more accessible to a wider community, allowing researchers to easily try

new ideas and improve existing ones. The ability to view and modify the

source code of the library also allows for greater transparency and

reproducibility in research, which is essential for the advancement of

knowledge.



Moreover, PyLFG’s open-source nature allows for collaboration and

contributions from the wider community. This can lead to the development

of new features and improvements in the library, making it a valuable

tool for linguistics students and professors, language learning

applications, and documenting under-resourced languages.



Open science is the best way of spreading and furthering knowledge, and

PyLFG aims to contribute to this goal by providing a valuable tool that

can be used by researchers and practitioners alike. The open-source

nature of PyLFG will ensure that it is accessible to anyone who is

interested in studying LFG, making it an essential tool for advancing

knowledge in the field of linguistics.



Important note

~~~~~~~~~~~~~~



PyLFG is still in early development and has not yet reached a stable

release state.



Features

--------



PyLFG is designed to be a comprehensive tool for working within the

Lexical Functional Grammar (LFG) formalism, providing a range of

features that make it a valuable tool for researchers and practitioners

alike.



-  Modularity: PyLFG is fully modular, allowing researchers to easily

   replace all parts of the LFG parsing pipeline, from tokenizing

   sentences to the rich visualizations of the x-structures. This allows

   for flexibility in trying new ideas and improving existing ones,

   making it a valuable tool for advancing knowledge in the field of

   linguistics.

-  Parsing and generation: PyLFG is not only able to parse sentences but

   also generate sentences from f-structures, which is an essential

   capability for automated translation and language learning

   applications.

-  Transfer capabilities: PyLFG has transfer capabilities which allow it

   to do automated translation between languages, making it a useful

   tool for researchers and practitioners working on natural language

   processing.

-  User-friendly interface: PyLFG provides both a TUI (Terminal User

   Interface) and a WebUI for easy interaction, making it accessible to

   a wide range of users, including students and professors who are

   taught Python in university.

-  Open-source: PyLFG is an open-source project, meaning that the source

   code is freely available for anyone to view and modify. This allows

   for greater transparency and reproducibility in research, and also

   enables collaboration and contributions from the wider community.

-  Suitable for linguistics students and professors: PyLFG is written in

   Python, which is a widely used programming language in the field of

   linguistics research. This makes it perfectly suited for linguistics

   students and professors, as well as python programmers in general.

-  Valuable tool for documenting under-resourced languages: PyLFG

   provides a valuable tool for documenting under-resourced languages,

   which is essential for preserving and studying these languages.



In summary, PyLFG is a comprehensive and user-friendly open-source tool

that provides a range of features that make it valuable for linguistics

students and professors, language learning applications, and documenting

under-resourced languages.



Use Cases

---------



PyLFG can be used in a variety of applications, making it a valuable

tool for researchers and practitioners working in a range of fields.

Some of the key use cases include:



-  Linguistics research: PyLFG is a valuable tool for linguistics

   students and professors who study syntactic theories. It can be used

   to parse sentences and generate f-structures, which can be used to

   test hypotheses and advance knowledge in the field.

-  Language learning applications: PyLFG’s ability to generate sentences

   from f-structures makes it a useful tool for language learning

   applications. It can be used to generate grammatically correct

   sentences for language learners to practice, and its transfer

   capabilities can also be used to translate between languages.

-  Documenting under-resourced languages: PyLFG’s ability to parse and

   generate sentences makes it a valuable tool for documenting

   under-resourced languages. It can be used to create grammatically

   correct sentences for use in language dictionaries and phrasebooks,

   and its transfer capabilities can also be used to translate between

   languages.

-  Natural language processing: PyLFG’s transfer capabilities and

   ability to generate sentences from f-structures make it a valuable

   tool for researchers and practitioners working on natural language

   processing. It can be used to automate the translation of sentences

   between languages, which has a wide range of applications, such as

   machine translation and language-based search engines.

-  Language-based search engines: PyLFG can be used to generate

   f-structures, which can be used to create grammatically correct

   sentences for use in language-based search engines. This makes it a

   valuable tool for researchers and practitioners working in this

   field.



In summary, PyLFG is a versatile tool that can be used in a wide range

of applications, making it a valuable tool for researchers and

practitioners working in linguistics, language learning, natural

language processing, and language-based search engines.



Technical Details

-----------------



PyLFG’s architecture is divided into five main components:



-  Tokenization: PyLFG uses the NLTK library to tokenize sentences. This

   allows users to tokenize sentences in multiple languages, including

   English, Spanish, French, and German.

-  Morphological Analysis: PyLFG uses a morphological analyzer to

   identify the base forms of words and their grammatical properties.

   This is an important step in the LFG parsing process, as it provides

   the necessary information for generating f-structures.

-  Parsing: PyLFG uses a modified version of the C-Structure Earley

   parser to parse sentences and generate f-structures. This parser is

   based on the Earley algorithm, which is a top-down parsing algorithm

   that is well-suited for parsing context-free grammars.

-  C-Structure and F-Structure Construction: PyLFG uses the information

   obtained from tokenization and morphological analysis to construct

   both C-structures and F-structures. These structures represent the

   syntactic and functional properties of sentences, respectively.

-  Visualization: PyLFG uses the Graphviz library to visualize

   f-structures. This allows users to create rich visualizations of

   f-structures, making it easy to understand and analyze the structures

   generated by the parser.



In addition, PyLFG also provides a TUI (Terminal User Interface) and a

WebUI (Web User Interface) which makes it easy for users to interact

with the library, parse sentences and visualize the f-structures



PyLFG is written in Python, which means users of the library can

leverage the wide range of libraries and frameworks available in Python,

such as NLTK and Spacy, which makes it a powerful and flexible tool for

working with LFG structures.



Contributing

------------



PyLFG is an open-source project and we welcome contributions from the

community. There are several ways to contribute, including:



-  Reporting bugs: If you find a bug in PyLFG, please report it on the

   GitHub issue tracker. Be sure to include as much information as

   possible, such as the version of PyLFG you are using, the steps to

   reproduce the bug, and any error messages you received.

-  Suggesting features: If you have an idea for a new feature in PyLFG,

   please suggest it on the GitHub issue tracker. Be sure to include as

   much detail as possible about the feature, including any relevant use

   cases or examples.

-  Writing code: If you would like to contribute code to PyLFG, please

   fork the repository on GitHub and submit a pull request. Be sure to

   follow the existing code style, and include tests and documentation

   for your changes.

-  Documentation: If you find any errors or inconsistencies in the

   documentation, or would like to suggest improvements, please let us

   know on the GitHub issue tracker.

-  Examples: If you have examples of using PyLFG in your research or

   projects, we would love to hear about them and feature them in the

   documentation.



We are looking forward to hearing from you and working together to

improve PyLFG. Thank you for considering to contribute to this project!



Please also note that by contributing to this project, you agree to

abide by our code of conduct.



Conclusion

----------



PyLFG is a powerful open-source Python library for working within the

Lexical Functional Grammar (LFG) formalism. It provides a comprehensive

set of classes and methods for representing and manipulating LFG

structures, including lexical functional structures (f-structures) and

c-structures. With its modular design, PyLFG allows researchers to

easily experiment with new ideas and customize their LFG parsing

pipeline.



By making PyLFG open-source, we aim to contribute to the goal of open

science and the spread and advancement of knowledge in the field of

linguistics.



We invite the community to contribute to the development of PyLFG by

reporting bugs, suggesting new features, writing code, improving

documentation and sharing examples of using PyLFG. We are looking

forward to working together to improve PyLFG and make it an even more

powerful tool for researchers in the field of linguistics.



Usage

-----



The package provides helper functions for loading grammar rules and

lexicon from files, and a ``LFGParseTree`` and ``LFGParseTreeNode``

class for representing and visualizing parse trees. Here is an example

of how to use the package:



.. code:: python



   from pylfg import build_parse_trees



   sentence = "the cat sits on the mat"



   # load grammar and lexicon

   grammar = load_grammar("path/to/grammar.txt")

   lexicon = load_lexicon("path/to/lexicon.txt")



   # parse sentence

   trees = build_parse_trees(sentence, grammar, lexicon)



   # print the first parse tree

   print(trees[0])



You can also use the LFGParseTree.to_f_structure method to export the

f-structure of the sentence in latex format, as shown in this example



.. code:: python



   f_structure = trees[0].to_f_structure()



   # write f-structure to a latex file

   with open("f_structure.tex", "w") as f:

       f.write(f_structure)