easyted 0.0.1

A Python library for easy calculation of tree edit distances with visualization capabilities.

EasyTED Library

The EasyTED Library offers a straightforward approach for calculating the syntactic tree edit distance (TED) between two sentences. Utilizing advanced Natural Language Processing (NLP) techniques, EasyTED parses sentences to their constituency trees, facilitating in-depth linguistic analyses with minimal setup. Beyond calculating distances, it features tree visualization and transformation tools, making it an indispensable resource for linguistics research and NLP applications.

Features

• Tree Edit Distance Calculation: Compute the TED between any two sentences.
• Constituency Tree Parsing: Transform sentences into their underlying constituency tree structures.
• Tree Visualization: Generate and save visual representations of constituency trees.
• Bracketed String Transformation: Convert constituency trees into a bracketed string format for easy comparison and analysis.
• Simple Integration: Designed to seamlessly integrate with broader NLP and linguistic analysis workflows.

Installation

Install EasyTED directly from the Python Package Index (PyPI) using pip:

pip install easyted

Usage

Calculating Tree Edit Distance

from easyted import TreeEditDistanceCalculator

# Initialize the calculator
calculator = TreeEditDistanceCalculator()

# Calculate the tree edit distance between two sentences
distance = calculator.calculate_ted("This is a test.", "This is only a test.")
print(f"Tree Edit Distance: {distance}")

Visualizing Constituency Trees

# Draw and save the constituency tree to a file
calculator.draw_and_save_tree("A visualization of a constituency tree.", "tree_visualization.ps")

Requirements

• Python 3.6+
• NLTK
• stanza
• APTED

Contributing

We welcome contributions to the EasyTED Library! If you have suggestions for improvements or wish to contribute new features, please feel free to open an issue or submit a pull request. Ensure your contributions adhere to the coding standards set forth by the project.

License

EasyTED is licensed under the MIT License. See the LICENSE file in the project repository for more details.

Acknowledgments

Thanks to NLTK for providing the foundational tools for working with natural language data. Appreciation to the Stanford NLP Group for the development of the stanza library, which powers the linguistic analysis capabilities of EasyTED. Gratitude to the developers of the APTED algorithm for their work on efficient tree edit distance computation.

Citations

If you use EasyTED in your research, please consider citing the following:

@inproceedings{qi2020stanza,
    title={Stanza: A {Python} Natural Language Processing Toolkit for Many Human Languages},
    author={Qi, Peng and Zhang, Yuhao and Zhang, Yuhui and Bolton, Jason and Manning, Christopher D.},
    booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics: System Demonstrations",
    year={2020}
}

@article{pawlik2016tree,
    title={Tree edit distance: Robust and memory- efficient},
    author={Pawlik, Mateusz and Augsten, Nikolaus},
    journal={Information Systems},
    volume={56},
    year={2016}
}

@article{pawlik2015efficient,
    title={Efficient Computation of the Tree Edit Distance},
    author={Pawlik, Mateusz and Augsten, Nikolaus},
    journal={ACM Transactions on Database Systems (TODS)},
    volume={40},
    number={1},
    year={2015}
}

@article{pawlik2011rted,
    title={RTED: A Robust Algorithm for the Tree Edit Distance},
    author={Pawlik, Mateusz and Augsten, Nikolaus},
    journal={PVLDB},
    volume={5},
    number={4},
    year={2011}
}