Tracing Metonymic Relations in T-PAS: An Annotation Exercise on a Corpus-based Resource for Italian
Authors: Emma Romani, Elisabetta Jezek (Università di Pavia, 2020)
Topic: Lexical and Semantic Resources and Analysis

Abstract
In this paper we address the main issues and results of a research thesis (Romani, 2020) dedicated to the annotation of metonymies in T-PAS, a corpus-based digital repository of Italian verbal patterns (Ježek et al., 2014). The annotation was performed on the corpus instances of a selected list of 30 verbs and was aimed at both implementing the resource with metonymic patterns and identifying and creating a map of the metonymic relations that occur in the verbal patterns. The annotated corpus data (consisting of 1218 corpus instances), the patterns, and the relations can be useful for NLP tasks such as metonymy recognition.

Introduction
Metonymy is a language phenomenon for which one referent is used to denote another referent associated with it (Lakoff & Johnson, 1980; Fauconnier, 1985; Ježek, 2016). For example, in the sentence ‘he drank a glass at the pub’, glass (the metonymic or source type denoting a container) refers to its content (the target type, a beverage). In our research, we investigated metonymy from a corpus-based perspective, through the analysis of corpus data and the annotation performed in T-PAS, a corpus-based resource for Italian verbs. T-PAS consists of a repository of typed predicate argument structures (Ježek et al., 2014), i.e. verbal patterns together with semantically-specified arguments, linked to manually annotated corpus instances (see Section 3.1). An example of a pattern (or t-pas) for the verb bere ‘to drink’ is reported in Figure 1, where [Animate] and [Beverage] are the semantic types specifying the subject and object positions. The annotation of metonymies was performed on the corpus instances of a list of 30 verbs contained in T-PAS (taken from Ježek & Quochi, 2010). As emerged from this background study, the semantic properties of those verbs were likely to convey metonymies in their argument structures. Starting from this list, our work was intended as an implementation of the resource; specifically, we annotated metonymic corpus instances and created metonymic sub-patterns linked to them. The research had several aims. First, we were interested in studying qualitatively the phenomenon in and through the corpus instances and in implementing the annotation tool of the resource with a specific feature that allowed us to encode metonymic arguments in the verbal patterns. For the latter purpose, we collaborated with the Faculty of Informatics at Masaryk University of Brno (CZ): they gave us the technical support for the implementation of the annotation tool. Second, our intention was to conceive a general theoretical framework to represent the metonymies found through the qualitative corpus analysis, by designing a map of metonymies and by drafting a list of the metonymic relations that occur in the verbal patterns (see Section 4). The paper is organized as follows. In Section 2 we present related studies. In Section 3 we describe the methodology we followed in annotating the corpus instances for metonymies, together with a brief introduction to T-PAS. In Section 4 we present the results of our annotation: a generalization of the metonymic relations found, and a map which visually highlights the semantic and cognitive connections between the semantic types. Further developments of the project are described in Section 5; our intention is to enrich the number of analysed verbs and eventually add new types of metonymic relations.

Conclusion
In this paper, we approached the study of metonymy from a corpus-based perspective. The research was conducted on a selected list of verbs, taken from a background study (Ježek & Quochi, 2010). Our aim was to search for metonymic phenomena inside a corpus of Italian language and to register them in a resource for Italian verbs, T-PAS. To do so, we conceived an annotation scheme and procedure that gave us relevant results and allowed us to register a variety of metonymic relations. We also attempted to make some theoretical generalizations based on the metonymic relations we found through the corpus analysis. We therefore created a list of metonymic relations and we designed a map in which the relations are connected to the semantic types they involve. Both the map and the list depict the complexity and variety of the phenomenon, in terms of number of possible metonymic relations and of the semantic types interested. In future perspectives, we intend to enrich the map and the list with new relations by extending the number of verbs investigated and to evaluate the annotation procedure. For future annotations, we will provide the current version of the list and of the map on the online public version of T-PAS (upcoming). We are also interested in comparing our results with those in Marini & Ježek (2020), in a cross-linguistic perspective. In line with previous studies (Section 2), we believe that the annotated corpus data, as well as the relations in Table 2, could be useful for automatic detection of metonymies. To our knowledge, little work has been done on this for Italian language: it would be therefore intriguing to test our data in NLP tasks.