Defining an annotation scheme with a view to automatic text simplification
Authors: Dominique Brunato, Felice Dell'orletta, Giulia Venturi, Simonetta Montemagni (CNR-ILC, 2014)
Topic: Text Simplification

Abstract
This paper presents the preliminary steps of ongoing research in the field of au- tomatic text simplification. In line with cur- rent approaches, we propose here a new an- notation scheme specifically conceived to identify the typologies of changes an original sentence undergoes when it is manually sim- plified. Such a scheme has been tested on a parallel corpus available for Italian, which we have first aligned at sentence level and then annotated with simplification rules.

Introduction
Automatic Text Simplification (ATS) as a field of research in NLP is receiving growing attention over the last few years due to the implications it has for both machine- and human-oriented tasks. For what concerns the former, ATS has been employed as a pre-processing step, which pro- vides an input that is easier to be analyzed by NLP modules, so that to improve the efficiency of, e.g., parsing, machine translation and infor- mation extraction. For what concerns the latter, ATS can also play a crucial role in educational and assistive technologies; e.g., it is used for the creation of texts adapted to the needs of particular readers, like children (De Belder and Moens, 2010), L2 learners (Petersen and Ostendorf, 2007), people with low literacy skills (Aluìsio et al., 2008), cognitive disabilities (Bott and Saggion, 2014) or language impairments, such as aphasia (Carroll et al., 1998) or deafness (Inui et al., 2003). From the methodological point of view, while the first attempts were mainly developed on a set of predefined rules based on linguistic intuitions (Chandrasekar et al., 1996; Siddharthan, 2002), current ones are much more prone to adopt datadriven approaches. Within the latter paradigm, the availability of monolingual parallel corpora (i.e. corpora of authentic texts and their manually simplified versions) turned out to be a necessary prerequisite, as they allow for investigating the actual editing operations human experts perform on a text in the attempt to make it more comprehensible for their target readership. This is the case of Brouwers et al. (2014) for French; Bott and Saggion (2014) for Spanish; Klerke and Søgaard (2012) for Danish and Caseli et al. (2009) for Brazilian Portuguese. To our knowledge, only a parallel corpus exists for Italian which was developed within the EU project Terence, aimed at the creation of suitable reading materials for poor comprehenders (both hearing and deaf, aged 7-11)1. An excerpt of this corpus was used for testing purposes by Barlacchi and Tonelli (2013), who devised the first rule-based system for ATS in Italian focusing on a limited set of linguistic structures. The approach proposed in this paper is inspired to the recent work of Bott and Saggion (2014) for Spanish and differs from the work of Barlacchi and Tonelli (2013) since it aims at learning from a parallel corpus the variety of text adaptations that characterize manual simplification. In particular, we focus on the design and development of a new annotation scheme for the Italian language intended to cover a wide set of linguistic phenomena implied in text simplification.

Conclusion
We have illustrated the first annotation scheme for Italian that includes a wide set of simplification rules spanning across different levels of linguistic description. The scheme was used to annotate the only existing Italian parallel corpus. We believe such a resource will give valuable insights into human text simplification and create the prerequisites for automatic text simplification. Current developments are devoted to refine the annotation scheme, on the basis of a qualitative and quantitative analysis of the annotation results; we are also testing the suitability of the annotation scheme with respect to other corpora we are also gathering in a parallel fashion. Based on the statistical findings on the productivity of each rule, we will investigate whether and in which way certain combinations of rules affect the distribution of multi-leveled linguistic features between the original and the simplified texts. In addition, we intend to explore the relation between text simplification and a related task, i.e. readability assessment, with the aim of comparing the effects of such combinations of rules on the readability scores.