Multi-Word Expressions in spoken language: PoliSdict
Authors: Daniela Trotta, Teresa Albanese, Michele Stingo, Raffaele Guarasci, Annibale Elia (Università di Salerno, Network Contacts, CNR-ICAR, 2018)
Topic: Lexical and Semantic Resources and Analysis

Abstract
The term multiword expressions (MWEs) is referred-to a group of words with a unitary meaning, not inferred from that of the words that compose it, both in current use and in technical-specialized languages. In this paper, we describe PoliSdict an Italian electronic dictionary composed of multi-word expressions (MWEs) automatically extracted from a multimodal corpus grounded on political speech language, currently being developed at the "Maurice Gross" Laboratory of the Department of Political Sciences, Social and Communication of the University of Salerno, thanks to a loan from the company Network Contacts. We introduce the methodology of creation and the first results of a systematic analysis which considered terminological labels, frequency labels, recurring syntactic patterns, further proposing an associated ontology.

Introduction
The term multi-word expressions (MWEs) includes a wide range of constructions such as noun compounds, adverbials, binomials, verb particles constructions, collocations, and idioms (Vietri, 2014). D'Agostino & Elia (1998) consider MWUs part of a continuum in which combinations can vary from a high degree of variability of co-occurrence of words (combinations with free distribution), to the absence of variability of co-occurrence1. They identify four different types of combinations of phrases or sentences, namely (i) with a high degree of variability of co-occurrence among words; (ii) with a limited degree of variability of co-occurrence among words; (iii) with no or almost no variability of co-occurrence among words; (iv) with no variability of co-occurrence among words. The essential role played by MWEs in Natural Language Processing (NLP) and linguistic analysis in general has been long recognised, as confirmed by then numerous dedicated workshops and special issues of journals discussing this subject in recent years (CSL, 2005; JLRE, 2009), and this appears more clear if we consider as the detection of MWEs represents a real issue in several NLP tasks such as semantic parsing and machine translation (Fellbaum, 2011). According to Chiari (2012) regarding the Italian language a line of great interest is represented by the works of Annibale Elia and Simonetta Vietri (Elia, D'Agostino et al 1985, Vietri 1986, D'Agostino and Elia 1998, Vietri 2004). Finally the discussion concerning the MWEs in Italian lexicography has been systematized in the GRADIT (De Mauro 1999) which records 132.000 different MWEs, whose collection was coordinated by Annibale Elia at the Department of Communication Sciences of the University of Salerno. This research is part of the larger project BIG 4 M.A.S.S. conducted by the company Network Contacts2 in collaboration with the Department of Social Politics and Communication, which received funding to develop semantic and syntactic modules of Italian.

Conclusion
In this work we described the initial steps for the development and formalization of PoliSdict, an electronic dictionary of spoken language MWEs. We illustrated the methdology used to build the resource and the preliminary results that we obtained from a systematic analysis. For what is related to future research we consider necessary exploiting standard association measures (like mutual information or log-likelihood ratio) to get an index of cohesion within the identified expressions and compare the use and collocations of MWEs between corpora of written and spoken language in order to understand which of them are the most used. Considering this study as an initial experiment on a relatively small sample, a larger balanced corpus would be necessary for a broader coverage, therefore we intend to proceed with the expansion of the corpus and the associated dictionary. Following we will make the described resources freely accessible by means of graphical interface, so as to offer the possibility to browse and explore data, also allowing the free use of the source codes for research purposes under Creative Commons License (CC+BY-NC-ND.