Title
EASSE: Easier automatic sentence simplification evaluation
Date Issued
01 January 2019
Access level
metadata only access
Resource Type
conference paper
Author(s)
University of Sheffield
Publisher(s)
Association for Computational Linguistics (ACL)
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 metrics 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.
Start page
49
End page
54
Language
English
OCDE Knowledge area
Sistemas de automatización, Sistemas de control
Scopus EID
2-s2.0-85083078131
ISBN of the container
9781950737925
Conference
EMNLP-IJCNLP 2019 - 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing, Proceedings of System Demonstrations
Sources of information:
Directorio de Producción Científica
Scopus