{"categories":[{"label":"Linguistic","url":"https://skillfed.io/packages/category/text-processing-linguistic/2"}],"enrichment":{"capability":"Computes ROUGE metrics (ROUGE-N, ROUGE-L, ROUGE-W, ROUGE-S, ROUGE-SU) for automatic evaluation of text summarization quality, with both a pure Python implementation and a Perl script wrapper.","skillfed_tags":["summarization-evaluation","nlp-metrics"],"use_cases":["Evaluate generated summaries against reference summaries in a summarization research project or benchmark.","Batch-score multiple hypothesis-reference pairs from files to compare summarization model outputs.","Integrate ROUGE scoring into an NLP pipeline for multi-lingual text summarization with custom tokenization.","Reproduce results from published summarization papers that report ROUGE-1, ROUGE-2, ROUGE-L metrics.","Compare summarization systems using command-line ROUGE scoring without writing Python code."],"what_it_does":"rouge-metric is a Python library for computing ROUGE (Recall-Oriented Understudy for Gisting Evaluation) metrics, the standard automatic evaluation framework for text summarization. It provides two implementations: a pure Python version that computes ROUGE-N, ROUGE-L, ROUGE-W, ROUGE-S, and ROUGE-SU scores without external process invocation, and a wrapper around the official ROUGE-1.5.5.pl Perl script for compatibility with existing workflows. The Python implementation is language-agnostic and treats documents as token sequences, letting you apply your own tokenization (e.g., nltk for English, jieba for Chinese) before scoring.\n\nThe package is designed for researchers and practitioners evaluating automatic summarization systems. It supports single and multiple references per hypothesis, batch evaluation over document collections, and both command-line and programmatic APIs. The pure Python path is fast and produces identical results to the Perl reference on single-document scenarios. However, the project is abandoned as of 2020 and receives no maintenance or updates.","worth_installing":"Yes, if you need ROUGE metrics for summarization evaluation and can tolerate an abandoned package. The library is stable, has low install friction, and produces correct results for its intended use. Install it for research or production summarization evaluation, but do not expect bug fixes or updates. Consider forking or switching to an actively maintained alternative if you encounter issues or need new features."},"id":"rouge-metric","links":{"html":"https://skillfed.io/packages/rouge-metric","md":"https://skillfed.io/packages/rouge-metric.md","pypi":"https://pypi.org/project/rouge-metric/"},"maintenance":{"status":"abandoned"},"meta":{"latest_release":"2020-10-21","license_spdx":null,"license_treatment":"permissive","name":"rouge-metric","python_support":"supports_current","summary":"A fast python implementation of full ROUGE metrics for automatic summarization."},"popularity":{"monthly_downloads":137312,"position":11371,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.0.1"}