Auxiliary selection in Italian intransitive verbs: a computational investigation based on annotated corpora
Authors: Ilaria Ghezzi, Cristina Bosco, Alessandro Mazzei (Università di Torino, 2018)
Topic: Lexical and Semantic Resources and Analysis

Abstract
The purpose of this paper is the analysis of the auxiliary selection in intransitive verbs in Italian. The applied methodology consists in comparing the linguistic theory with the data extracted from two different annotated corpora: UD-IT and PoSTWITA-UD. The analyzed verbs have been classiﬁed in different semantic categories depending on the linguistic theory. The results conﬁrm the theoretical assumptions and they could be considered as a starting point for many applicative tasks as Natural Language Generation.

Introduction
In this work we have applied a corpus-based approach to the investigation of the behavior of Italian intransitive verbs for what concerns the selection of the auxiliary verb. We considered two corpora, namely UD-IT1 and PoSTWITA-UD (Sanguinetti et al., 2018), annotated following the 1http://universaldependencies.org/it/ overview/introduction.html Universal Dependencies standards. UD-IT and PoSTWITA-UD are treebanks (morphologically and syntactically annotated corpora) for the Italian language. UD-IT is made up of texts from various sources, namely the Italian Constitution, the Italian Civil Code, newspaper articles and Wikipedia. It is a balanced corpus and, therefore, a representative corpus for Italian standard language. On the other hand, PoSTWITA-UD contains tweets from the social media Twitter, and can therefore be considered a representative corpus for the Italian Language used in social media (non-standard Italian). This difference allows us to investigate verbs’ behaviour in standard and non-standard Italian Language. Intransitive verbs have been extensively studied in both traditional grammar and linguistics, since they do not always follow a standardized rule for the auxiliary selection (see examples Section 2). This fact could be the reason why their status is not currently formalized enough in NLP, as long as Italian is concerned. Among the most recent investigation which use a corpus linguistic methodology for the Italian language, we ﬁnd (Amore, 2017). Our analysis starts from traditional Italian grammars and then moves to the Auxiliary Selection Hierarchy by (Sorace, 2000), a syntactic and semantic perspective on the behaviour of intransitive verbs and auxiliary selection in Romance languages. That can be useful for formalizing the studied phenomenon and thus providing Natural Language Generation systems with the necessary information regarding the auxiliary selection, which is our ﬁnal goal. Another contribute for the same systems but for what concerns adjectives has been published in (Conte et al., 2017).

Conclusion
The paper presents a study about the auxiliary selection in intransitive verbs in Italian. Providing that the qualitative description given by traditional grammars does not allow the deﬁnition of a formal model for the auxiliary selection, we considered a study (Sorace, 2000) that classiﬁes the intransitive verbs taking into account both semantic and syntactic features and behaviors. The long-term goal of this study is to contribute to the development of a natural language generation system for Italian (Mazzei et al., 2016; Mazzei, 2016; Conte et al., 2017). In particular, the facilities of a ﬂuent automatic selection of the auxiliary can be an important feature also in context where the realizer module of the system is used for extracting suggestions for non-native speakers learning Italian as 6English translation: If, under request of the sender, the carrier issues the airway bill, it is considered, if not proven otherwise, that he has acted in the name of the sender. L2. We adopted in this study a corpus-based perspective and we tested our assumption on two treebanks for Italian respectively representig standard and social media language. The results conﬁrm and validate the theory and they could be used to develop a formal model that can be exploited in a computational context.