Towards an Italian Learner Treebank in Universal Dependencies
Authors: Elisa Di Nuovo, Cristina Bosco, Alessandro Mazzei, Manuela Sanguinetti (Università di Torino, 2019)
Topic: Learner Corpora and Language Acquisition

Abstract
In this paper we describe the preliminary work on a novel treebank which includes texts written by learners of Italian drawn from the VALICO corpus. Data processing mostly involved the application of Universal Dependencies formalism and error annotation. First, we parsed the texts on UDPipe trained on the existent Italian UD treebanks, then we manually corrected them. The particular focus of this paper is on a one-hundred-sentence sample of the collection, used as a case study to define an annotation scheme for identifying the linguistic phenomena characterizing learners’ interlanguage.

Introduction
The increasing interest in Learner Corpora (henceforth LC) is twofold motivated. On the one hand, LC are an especially valuable source of knowledge for interlanguage varieties. They allow in-depth comparisons of non-native varieties, helping to elucidate the properties of the interlanguage developed by learners with different mother tongues and learning levels. For this reason, LC are important resources enabling data-driven studies exploited within several research areas, such as Second Language Acquisition, Foreign Language Teaching, Contrastive Interlanguage Analysis, Computer-aided Error Analysis, Computer-Assisted Language Learning and L2 Lexicography (e.g. (Pravec, 2002; Granger, 2008; McEnery and Xiao, 2011)). On the other hand, LC have raised considerable computational interest, which is closely related to their usefulness in tasks such as Native Language Identification (Jarvis and Paquot, 2015; Malmasi, 2016), Grammatical-Error Detection and Correction (Leacock et al., 2015; Ng et al., 2014), and Automated Essay Scoring (Higgins et al., 2015). In this paper we describe the development of a novel learner Italian treebank, i.e. VALICO-UD, in which Universal Dependencies (UD) formalism is tied to error annotation. The considerations of the annotation process, carried out on a set of one hundred sentences selected from a subcorpus of VALICO1 (see Table 1) (Corino and Marello, 2017), allowed us to test a pilot scheme which pinpoints some of the features of L2 Italian. This paper is organized as follows: in Section 2 we provide an overview of LC, focusing on Italian resources in particular; in Section 3 we present the data and the error annotation of VALICO-UD; in Section 4 we offer some examples of how we applied literal annotation to the learner sentences (LS) and, finally, in Section 6 we present conclusion and future work.

Conclusion
In this paper we introduced VALICO-UD and proposed an annotation scheme suitable for texts of learner Italian encompassing both UD and error annotation. Our scheme follows the principle of “literal annotation” and takes PoS and dependency morphological-distributional mismatches into account. Our error tag set seems adequate to bookmark errors, providing also a fine-grained description of some of them. There are a number of possible applications for the monolingual parallel treebank proposed in this paper. In the near future, we plan to apply the tree edit distance to LS and TH to measure linguistic competence. Recently, the tree edit distance has been applied to various tasks (Emms, 2008; Tsarfaty et al., 2011; Plank et al., 2015), and a study has formalized the notion of syntactic anisomorphism (Ponti et al., 2018). We aim to explore a correlation between these notions and the linguistic competence to describe the achievements of foreign language learners.