MUSST: A Multilingual Syntactic Simplification Tool

Carolina Scarton, Alessio Palmero Aprosio, Sara Tonelli, Tamara Martín Wanton, Lucia Specia


Abstract
We describe MUSST, a multilingual syntactic simplification tool. The tool supports sentence simplifications for English, Italian and Spanish, and can be easily extended to other languages. Our implementation includes a set of general-purpose simplification rules, as well as a sentence selection module (to select sentences to be simplified) and a confidence model (to select only promising simplifications). The tool was implemented in the context of the European project SIMPATICO on text simplification for Public Administration (PA) texts. Our evaluation on sentences in the PA domain shows that we obtain correct simplifications for 76% of the simplified cases in English, 71% of the cases in Spanish. For Italian, the results are lower (38%) but the tool is still under development.
Anthology ID:
I17-3007
Volume:
Proceedings of the IJCNLP 2017, System Demonstrations
Month:
November
Year:
2017
Address:
Tapei, Taiwan
Venue:
IJCNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
25–28
Language:
URL:
https://aclanthology.org/I17-3007
DOI:
Bibkey:
Cite (ACL):
Carolina Scarton, Alessio Palmero Aprosio, Sara Tonelli, Tamara Martín Wanton, and Lucia Specia. 2017. MUSST: A Multilingual Syntactic Simplification Tool. In Proceedings of the IJCNLP 2017, System Demonstrations, pages 25–28, Tapei, Taiwan. Association for Computational Linguistics.
Cite (Informal):
MUSST: A Multilingual Syntactic Simplification Tool (Scarton et al., IJCNLP 2017)
Copy Citation:
PDF:
https://aclanthology.org/I17-3007.pdf