Evaluating ImagAct-WordNet mapping for English and Italian through videos
Authors: Irene De Felice, Roberto Bartolini, Irene Russo, Valeria Quochi, Monica Monachini (CNR-ILC, 2014)
Topic: Lexical and Semantic Resources and Analysis

Abstract
In this paper we present the results of the evaluation of an auto-matic mapping between two lexical re-sources, WordNet/ItalWordNet and Ima-gAct, a conceptual ontology of action types instantiated by video scenes. Results are compared with those obtained from a previous experiment performed only on Italian data. Differences between the two evaluation strategies, as well as between the quality of the mappings for the two languages considered in this paper, are dis-cussed.

Introduction
In lexicography, the meaning of words is repre-sented through words: definitions in dictionaries try to make clear the denotation of lemmas, report-ing examples of linguistic usages that are funda-mental especially for function words like preposi-tions. Corpus linguistics derives definitions from a huge amount of data. This operation improves words meaning induction and refinements, but still supports the view that words can be defined by words. In the last 20 years dictionaries and lexicographic resources such as WordNet have been enriched with multimodal content (e.g. illustrations, pic-tures, animations, videos, audio files). Visual representations of denotative words like concrete nouns are effective: see for example the ImageNet project, that enriches WordNets glosses with pic-tures taken from the web. Conveying the meaning of action verbs with static representations is not possible; for such cases the use of animations and videos has been proposed (Lew 2010). Short videos depicting basic actions can support the users need (especially in second language acquisition) to understand the range of applicability of verbs. In this paper we describe the multimodal enrichment of Ital- WordNet and WordNet 3.0 action verbs entries by means of an automatic mapping with ImagAct (www.imagact.it), a conceptual ontology of action types instantiated by video scenes (Moneglia et al. 2012). Through the connection between synsets and videos we want to illustrate the meaning described by glosses, specifying when the video represents a more specific or a more generic action with respect to the one described by the gloss. We evaluate the mapping watching videos and then finding out which, among the synsets related to the video, is the best to describe the action performed.

Conclusion
Mutual enrichments of lexical resources is convenient, especially when different kinds of information are available. In this paper we describe the mapping between ImagAct videos representing action verbs’ meanings and Word- Net/ItalWordNet, in order to enrich the glosses multimodally. Two types of evaluation have been performed, one based on a gold standard that establishes correspondences between ImagActs basic action types and ItalWordNets synsets (Bartolini at al. 2014) and the other one based on the suitability of a synsets gloss to describe the action watched in the videos. The second type of evaluation suggests that for Italian the automatic mapping is effective in projecting the videos on Ital- WordNet’s glosses. For what regards the mapping for English, as future work we plan to change the settings, in order to test if the number of synonyms available in WordNet has a negative impact on the quality of the mapping.