Annotating opposition among verb senses: a crowdsourcing experiment
Authors: Anna Feltracco, Elisabetta Jezek, Bernardo Magnini, Simone Magnolini (Fondazione Bruno Kessler, Università di Pavia, Università di Brescia, 2015)
Topic: Lexical and Semantic Resources and Analysis

Abstract
We describe the acquisition, based on crowdsourcing, of opposition relations among Italian verb senses in the T-PAS resource. The annotation suggests the feasibility of a large-scale enrichment.

Introduction
Several studies have been carried out on the definition of opposition in linguistics, philosophy, cognitive science and psychology. Our notion of opposition is based on lexical semantic studies by Lyons (1977), Cruse (1986; 2002; 2011), and Pustejovsky (2000), as synthesized in Jezek (2015). The category of opposites can be said to include pairs of terms that contrast each other with respect to one key aspect of their meaning, such that together they exhaust this aspect completely. Examples include the following pairs: to open / to close, to rise / to fall. Paradoxically, the first step in the process of identifying a relationship of opposition often consists in identifying something that the meanings of the words under examination have in common. A second step is to identify a key aspect in which the two meanings oppose each other1 . Opposites cannot be true simultaneously of the same entity, for example a price cannot be said to rise and to fall at exactly the same point in time. It is an open discussion whether opposition is a semantic or a lexical relation (Murphy, 2010; Fellbaum, 1998); what is clear is that the predicate that is considered opposite of another predicate does not activate this relation for all its senses. For example, the Italian verb abbattere is considered opposite to costruire as far as the former is considered in its sense of to destroy (a building), and the latter in its sense of to build (a building). The opposition relation does not hold if abbattere is considered in its sense of to kill (an animal). Oppositions between verbs senses are poorly encoded in lexical resources. English WordNet 3.1 (Miller et al., 1990) tags oppositions among verb senses using the label antonymy; for example, increase#1 is in antonymy relation with decrease#1, diminish#1, lessen#1, fall#11. In VerbOcean (Chklovski and Pantel, 2004), opposition (antonymy) is considered a symmetric relation between verbs, which includes several subtypes; the relation is extracted at verb level (not at sense level). FrameNet (Ruppenhofer et al., 2010), on the other hand, has no tag for the opposition relation, although a subset of cases can be traced via the perspective on relation. As regards Italian, in MultiWordNet (Pianta et al., 2002) the opposition relation (labeled: antonymy relation) is considered a lexical relation and is represented in the currently available version for English, but not for Italian. In SIMPLE (Lenci et al., 2000), the opposition relation (antonymy) is considered a relation between word senses and it has been defined for adjectives (e.g., dead/alive and hot/cold), although the authors specify it can possibly be extended also to other parts of speech. In Senso Comune (Oltramari et al., 2013) the annotation of the opposition relation appears not to be implemented, even if the tag for the relation (antonimia) is present. The experiment described in the paper focuses on the annotation of opposition relations among verb senses. We annotate these relations in the lexical resource T-PAS (Jezek et al., 2014), an inventory of typed predicate argument structures for Italian manually acquired from corpora through inspection and annotation of actual uses of the analyzed verbs. The corpus instances associated to each T-PAS represent a rich set of grounded information not available in other resources and facilitate the interpretation of the different senses of the verbs 2 . We collected data using crowdsourcing, a methodology already used in other NLP tasks, such as Frame Semantic Role annotation (Fossati et al., 2013; Feizabadi and Padó, 2014), Lexical Substitution (Kremer et al., 2014), Contradictory Event Pairs Acquisition (Takabatake et al., 2015).

Conclusion
In this paper we have presented a crowdsourcing experiment for the annotation of the opposition relation among verb senses in the Italian T-PAS resource. The annotation experiment has shown the feasibility of collecting opposition relation among Italian verb senses through crowdsourcing. We propose a methodology based on the automatic substitution of a verb with a candidate opposite and show that the IAA obtained using sense examples is comparable with the IAA obtained by other annotations based on sense definitions. Ongoing work includes further annotation of the opposition relations in T-PAS using crowd answers and a deep examination of the causes which lead to the generation of sentences with no sense.