ER-Evaluation

ER-Evaluation: End-to-End Evaluation of Entity Resolution Systems - Published in JOSS (2023)

https://github.com/OlivierBinette/er-evaluation

Keywords

Scientific Fields

Repository

An End-to-End Evaluation Framework for Entity Resolution Systems

README.rst

.. image:: https://github.com/Valires/er-evaluation/actions/workflows/python-package.yaml/badge.svg
        :target: https://github.com/Valires/er-evaluation/actions/workflows/python-package.yaml
        :alt: Github Action workflow status and link.

.. image:: https://badge.fury.io/py/er-evaluation.svg
        :target: https://badge.fury.io/py/er-evaluation
        :alt: PyPI release badge and link.

.. image:: https://readthedocs.org/projects/er-evaluation/badge/?version=latest
        :target: https://er-evaluation.readthedocs.io/en/latest/?version=latest
        :alt: Documentation status badge and link.

.. image:: https://joss.theoj.org/papers/10.21105/joss.05619/status.svg
       :target: https://doi.org/10.21105/joss.05619
       :alt: Journal of Open Source Software publication badge and link.

🔍 ER-Evaluation: An End-to-End Evaluation Framework for Entity Resolution Systems
===================================================================================

`ER-Evaluation `_ is a Python package for the evaluation of entity resolution (ER) systems.

It provides an **entity-centric** approach to evaluation. Given a sample of resolved entities, it provides: 

* **summary statistics**, such as average cluster size, matching rate, homonymy rate, and name variation rate.
* **comparison statistics** between entity resolutions, such as proportion of links from one which is also in the other, and vice-versa.
* **performance estimates** with uncertainty quantification, such as precision, recall, and F1 score estimates, as well as B-cubed and cluster metric estimates.
* **error analysis**, such as cluster-level error metrics and analysis tools to find root cause of errors.
* convenience **visualization tools**.

For more information on how to resolve a sample of entities for evaluation and model training, please refer to our `data labeling guide `_.

Installation
---------------

Install the released version from PyPI using:

.. code:: bash

    pip install er-evaluation

Or install the development version using:
.. code:: bash

    pip install git+https://github.com/Valires/er-evaluation.git


Documentation
----------------

Please refer to the documentation website `er-evaluation.readthedocs.io `_.

Usage Examples
-----------------

Please refer to the `User Guide `_ or our `Visualization Examples `_ for a complete usage guide.

In summary, here's how you might use the package.

1. Import your predicted disambiguations and reference benchmark dataset. The benchmark dataset should contain a sample of disambiguated entities.

.. code::

        import er_evaluation as ee

        predictions, reference = ee.load_pv_disambiguations()

2. Plot `summary statistics `_ and compare disambiguations.

.. code::

        ee.plot_summaries(predictions)

.. image:: media/plot_summaries.png
   :width: 400

.. code::

        ee.plot_comparison(predictions)

.. image:: media/plot_comparison.png
   :width: 400

3. Define sampling weights and `estimate performance metrics `_.

.. code::

        ee.plot_estimates(predictions, {"sample":reference, "weights":"cluster_size"})

.. image:: media/plot_estimates.png
   :width: 400

4. Perform `error analysis `_ using cluster-level explanatory features and cluster error metrics.

.. code::

        ee.make_dt_regressor_plot(
                y,
                weights,
                features_df,
                numerical_features,
                categorical_features,
                max_depth=3,
                type="sunburst"
        )

.. image:: media/plot_decisiontree.png
   :width: 400

Development Philosophy
-------------------------

**ER-Evaluation** is designed to be a unified source of evaluation tools for entity resolution systems, adhering to the Unix philosophy of simplicity, modularity, and composability. The package contains Python functions that take standard data structures such as pandas Series and DataFrames as input, making it easy to integrate into existing workflows. By importing the necessary functions and calling them on your data, you can easily use ER-Evaluation to evaluate your entity resolution system without worrying about custom data structures or complex architectures.

Citation
-----------

Please acknowledge the publications below if you use ER-Evaluation:

- Binette, Olivier. (2022). ER-Evaluation: An End-to-End Evaluation Framework for Entity Resolution Systems. Available online at `github.com/Valires/ER-Evaluation `_
- Binette, Olivier, Sokhna A York, Emma Hickerson, Youngsoo Baek, Sarvo Madhavan, Christina Jones. (2022). Estimating the Performance of Entity Resolution Algorithms: Lessons Learned Through PatentsView.org. arXiv e-prints: `arxiv:2210.01230 `_
- Upcoming: "An End-to-End Framework for the Evaluation of Entity Resolution Systems With Application to Inventor Name Disambiguation"

Public License
--------------

* `GNU Affero General Public License v3 `_

Owner

Citation (CITATION.cff)

cff-version: "1.2.0"
authors:
- family-names: Binette
  given-names: Olivier
  orcid: "https://orcid.org/0000-0001-6009-5206"
- family-names: Reiter
  given-names: Jerome P.
  orcid: "https://orcid.org/0000-0002-8374-3832"
contact:
- family-names: Binette
  given-names: Olivier
  orcid: "https://orcid.org/0000-0001-6009-5206"
doi: 10.5281/zenodo.10086102
message: If you use this software, please cite our article in the
  Journal of Open Source Software.
preferred-citation:
  authors:
  - family-names: Binette
    given-names: Olivier
    orcid: "https://orcid.org/0000-0001-6009-5206"
  - family-names: Reiter
    given-names: Jerome P.
    orcid: "https://orcid.org/0000-0002-8374-3832"
  date-published: 2023-11-11
  doi: 10.21105/joss.05619
  issn: 2475-9066
  issue: 91
  journal: Journal of Open Source Software
  publisher:
    name: Open Journals
  start: 5619
  title: "ER-Evaluation: End-to-End Evaluation of Entity Resolution
    Systems"
  type: article
  url: "https://joss.theoj.org/papers/10.21105/joss.05619"
  volume: 8
title: "ER-Evaluation: End-to-End Evaluation of Entity Resolution
  Systems"

GitHub Events

Committers

Last synced: 5 months ago

Issues and Pull Requests

Last synced: 4 months ago