ERNESTA: A Sentence Simplification Tool for Children’s Stories in Italian

  • Gianni Barlacchi
  • Sara Tonelli
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7817)


We present ERNESTA (Enhanced Readability through a Novel Event-based Simplification Tool), the first sentence simplification system for Italian, specifically developed to improve the comprehension of factual events in stories for children with low reading skills. The system performs two basic actions: First, it analyzes a text by resolving anaphoras (including null pronouns), so as to make all implicit information explicit. Then, it simplifies the story sentence by sentence at syntactic level, by producing simple statements in the present tense on the factual events described in the story. Our simplification strategy is driven by psycholinguistic principles and targets children aged 7 - 11 with text comprehension difficulties. The evaluation shows that our approach achieves promising results. Furthermore, ERNESTA could be exploited in different tasks, for instance in the generation of educational games and reading comprehension tests.


Sentence simplification Anaphora Resolution Children Stories Italian Language 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Aluisio, S., Specia, L., Gasperin, C., Scarton, C.: Readability assessment for text simplification. In: Proceedings of the 5th Workshop on Innovative Use of NLP for Building Educational Applications, Stroudsburg, PA, USA, pp. 1–9 (2010)Google Scholar
  2. 2.
    Attardi, G., Dell’Orletta, F., Simi, M., Chanev, A., Ciaramita, M.: Multilingual Dependency Parsing and Domain Adaptation using DeSR. In: Proceedings of the CoNLL Shared Task Session of of EMNLP-CoNLL (2007)Google Scholar
  3. 3.
    Belder, J.D., Moens, M.F.: Text simplification for children. In: Proceedings of the SIGIR 2010 Workshop on Accessible Search Systems (2010)Google Scholar
  4. 4.
    Bernhard, D., de Viron, L., Moriceau, V., Tannier, X.: Question Generation for French: Collating Parsers and Paraphrasing Questions. Dialogue and Discourse 3(2), 43–74 (2012)Google Scholar
  5. 5.
    Brouwers, L., Bernhard, D., Ligozat, A.L., François, T.: Simplification syntaxique de phrases pour le français. In: Actes de la Conférence Conjointe JEP-TALN-RECITAL, Montpellier, France, pp. 211–224 (2012)Google Scholar
  6. 6.
    Cain, K.: Making sense of text: skills that support text comprehension and its development. Perspectives on Language and Literacy (2009)Google Scholar
  7. 7.
    Cain, K., Oakhill, J.: Profiles of children with specific reading comprehension difficulties. British Journal of Educational Psychology 76(683-696) (2006)Google Scholar
  8. 8.
    Carretti, B., Borella, E., Cornoldi, C., De Beni, R.: Role of working memory in explaining the performance of individuals with specific reading comprehension difficulties: A meta-analysis. Learning and Individual Differences 19(2), 246–251 (2009)CrossRefGoogle Scholar
  9. 9.
    Clarke, J.: Global Inference for Sentence Compression: An Integer Linear Programming Approach. Ph.D. thesis, University of Edinburgh (2008)Google Scholar
  10. 10.
    Dell’Orletta, F., Montemagni, S., Venturi, G.: READ–IT: Assessing Readability of Italian Texts with a View to Text Simplification. In: Proceedings of the Second Workshop on Speech and Language Processing for Assistive Technologies, Edinburgh, Scotland, UK, pp. 73–83 (July 2011)Google Scholar
  11. 11.
    Dorr, B., Zajic, D.: Hedge Trimmer: A parse-and-trim approach to headline generation. In: Proceedings of the Workshop on Automatic Summarization (2003)Google Scholar
  12. 12.
    Ehrlich, M.F., Rémond, M.: Skilled and less skilled comprehenders: French children’s processing of anaphoric devices in written texts. British Journal of Developmental Psychology 15, 291–309 (1997)CrossRefGoogle Scholar
  13. 13.
    Ehrlich, M.F., Remond, M., Tardieu, H.: Processing of anaphoric devices in young skilled and less skilled comprehenders: Differences in metacognitive monitoring. Reading and Writing 11, 29–63 (1999)CrossRefGoogle Scholar
  14. 14.
    Glöckner, I., Hartrumpf, S., Helbig, H., Leveling, J., Osswald, R.: An architecture for rating and controlling text readability. In: Proceedings of KONVENS 2006, Konstanz, Germany, pp. 32–35 (2006)Google Scholar
  15. 15.
    Heilman, M., Smith, N.A.: Extracting Simplified Statements for Factual Question Generation. In: Proceedings of QG 2010: The Third Workshop on Question Generation, Pittsburgh, Pennsylvania, USA (2010)Google Scholar
  16. 16.
    Beigman Klebanov, B., Knight, K., Marcu, D.: Text simplification for information-seeking applications. In: Meersman, R. (ed.) OTM 2004. LNCS, vol. 3290, pp. 735–747. Springer, Heidelberg (2004)CrossRefGoogle Scholar
  17. 17.
    Lavelli, A., Hall, J., Nilsson, J., Nivre, J.: MaltParser at the EVALITA 2009 Dependency Parsing Task. In: Proceedings of EVALITA Evaluation Campaign (2009)Google Scholar
  18. 18.
    Lucisano, P., Piemontese, M.E.: Gulpease. Una formula per la predizione della difficoltà dei testi in lingua italiana. Scuola e Città 3, 57–68 (1988)Google Scholar
  19. 19.
    Lyon, G.R., Fletcher, J.M., Barnes, M.C.: Learning Disabilities. In: Mash, E., Barkley, R.A. (eds.) Child Psychopathology, The Guilford Press, NY (2003)Google Scholar
  20. 20.
    Nation, K., Clarke, P., Marshall, C.M., Durand, M.: Hidden language impairments in children: parallels between poor reading comprehension and specific language impairment? Journal of Speech, Language and Hearing Research 47, 199–211 (2004)Google Scholar
  21. 21.
    Pianta, E., Girardi, C., Zanoli, R.: The TextPro tool suite. In: Proc. of the 6th Language Resources and Evaluation Conference (LREC), Marrakech, Morocco (2008)Google Scholar
  22. 22.
    Pimperton, H., Nation, K.: Suppressing irrelevant information from working memory. Evidence for domain-specific deficits in poor comprehenders. Journal of Memory and Language 62(380–391) (2010)Google Scholar
  23. 23.
    Poesio, M., Delmonte, R., Bristot, A., Chiran, L., Tonelli, S.: The VENEX corpus of anaphora and deixis in spoken and written Italian, University of Essex (2004) (manuscript)Google Scholar
  24. 24.
    Siddharthan, A.: Complex lexico-syntactic reformulation of sentences using typed dependency representations. In: Proceedings of the 6th International Natural Language Generation Conference (INLG 2010), Dublin, Ireland (2010)Google Scholar
  25. 25.
    Siddharthan, A.: Text Simplification using Typed Dependencies: A Comparision of the Robustness of Different Generation Strategies. In: Proceedings of the 13th European Workshop on Natural Language Generation (2011)Google Scholar
  26. 26.
    Snover, M., Dorr, B., Schwartz, R., Micciulla, L., Makhoul, J.: A study of translation edit rate with targeted human annotation. In: Proceedings of Association for Machine Translation in the Americas (2006)Google Scholar
  27. 27.
    Tonelli, S., Tran Manh, K., Pianta, E.: Making readability indices readable. In: Proceedings of the First Workshop on Predicting and Improving Text Readability for Target Reader Populations, Montréal, Canada, pp. 40–48 (June 2012)Google Scholar
  28. 28.
    Uryupina, O., Poesio, M.: Evalita 2011: Anaphora Resolution Task. In: Proceedings of EVALITA Evaluation Campaign (2011)Google Scholar
  29. 29.
    Yuill, N.M., Oakill, J.V.: Effects of inference awareness training on poor reading comprehension. Applied Cognitive Psychology 2, 33–45 (1988)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Gianni Barlacchi
    • 1
  • Sara Tonelli
    • 2
  1. 1.Information Engineering DepartmentUniversità di SienaItaly
  2. 2.Fondazione Bruno KesslerPovoItaly

Personalised recommendations