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Automated lexical simplification has been performed so far focusing only on the replacement of single tokens with single tokens, and this choice has affected both the development of systems and the creation of benchmarks. In this paper, we argue that lexical simplification in real settings should deal both with single and multi-token terms, and present a benchmark created for the task. Besides, we describe how a freely available system can be tuned to cover also the simplification of phrases, and perform an evaluation comparing different experimental settings.
traitement de texte, tecnology, linguaggio, traitement du langage naturel, digital humenities, intelligence artificielle, linguistica computazionale, natural language processing, language, Benchmark creation, tecnologia, langue, artificial intelligence, elaborazione del linguaggio naturale, Computational Linguistics, Lexical simplification, linguistique computationelle, text processing, umanistica digitale, Phrase extraction, intelligenza artificiale, elaborazione del testo, technologie
traitement de texte, tecnology, linguaggio, traitement du langage naturel, digital humenities, intelligence artificielle, linguistica computazionale, natural language processing, language, Benchmark creation, tecnologia, langue, artificial intelligence, elaborazione del linguaggio naturale, Computational Linguistics, Lexical simplification, linguistique computationelle, text processing, umanistica digitale, Phrase extraction, intelligenza artificiale, elaborazione del testo, technologie
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