Metadata-Version: 2.1
Name: seqscore
Version: 0.3
Summary: SeqScore: Scoring for named entity recognition and other sequence labeling tasks
Home-page: https://github.com/bltlab/seqscore
Author: Constantine Lignos
Author-email: lignos@brandeis.edu
License: MIT
Description: # SeqScore
        
        SeqScore: Scoring for named entity recognition and other sequence labeling tasks
        
        
        # Installation
        
        To install the latest release of SeqScore, run:
        `pip install seqscore`
        
        At this point, the released version is relatively out-of-date, but
        will be updated once new documentation is ready.
        
        For the latest version, check out the `main` branch (stable, but
        sometimes newer than the version on PyPI), or the `dev` branch
        (latest, but less tested).
        
        To install from a clone of this repository, use:
        `pip install -e .`
        
        
        # Usage
        
        ## Overview
        
        For a list of commands, run `seqscore --help`.
        
        Some examples:
        ```
        # Score like conlleval
        seqscore score --labels BIO --repair-method conlleval --reference <reference_conll_file> <prediction_conll_file>
        # Score discarding invalid chunks, which sometimes produces higher scores
        seqscore score --labels BIO --repair-method discard --reference <reference_conll_file> <prediction_conll_file>
        seqscore validate --labels BIO <input_conll_file>
        seqscore dump --labels BIO <input_conll_file> <output_delim_file>
        ```
        
        Scoring only supports BIO chunk encoding. Validation can be done for IO, BIO, and BIOES.
        At the moment, `dump` only supports BIO, but support will be added for IO and BIOES.
        
        
        # Features coming soon!
        
        * More documentation
        * More error analysis tools
        
        
        # Citation
        
        If you use SeqScore, please cite
        [Addressing Barriers to Reproducible Named Entity Recognition Evaluation](https://arxiv.org/abs/2107.14154).
        
        
        # License
        
        SeqScore is distributed under the MIT License.
        
        
        # Setting up for development
        
        1. Create environment: `conda create -y -n seqscore python=3.8`
        2. Activate the environment: `conda activate seqscore`
        3. Install dependencies: `pip install -r requirements.txt`
        4. Install seqscore: `pip install -e .`
        
Platform: UNKNOWN
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Requires-Python: ~=3.8
Description-Content-Type: text/markdown
