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Conference papers

EASSE: Easier Automatic Sentence Simplification Evaluation

Abstract : We introduce EASSE, a Python package aiming to facilitate and standardise automatic evaluation and comparison of Sentence Simplification (SS) systems. EASSE provides a single access point to a broad range of evaluation resources: standard automatic metrics for assessing SS outputs (e.g. SARI), word-level accuracy scores for certain simplification transformations, reference-independent quality estimation features (e.g. compression ratio), and standard test data for SS evaluation (e.g. TurkCorpus). Finally, EASSE generates easy-to-visualise reports on the various met-rics and features above and on how a particular SS output fares against reference simplifications. Through experiments, we show that these functionalities allow for better comparison and understanding of the performance of SS systems.
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Submitted on : Wednesday, January 22, 2020 - 4:43:38 PM
Last modification on : Wednesday, June 8, 2022 - 12:50:06 PM
Long-term archiving on: : Thursday, April 23, 2020 - 4:50:08 PM


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  • HAL Id : hal-02272950, version 1



Fernando Alva-Manchego, Louis Martin, Carolina Scarton, Lucia Specia. EASSE: Easier Automatic Sentence Simplification Evaluation. EMNLP-IJCNLP 2019 - Conference on Empirical Methods in Natural Language Processing and 9th International Joint Conference on Natural Language Processing (demo session), Nov 2019, Hong Kong, China. pp.49-54. ⟨hal-02272950⟩



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