The paper presents a pilot exploration of the construction, management and analysis of a multimodal corpus. Through athree-layer annotation that provides orthographic, prosodic, and gestural transcriptions, the gest-IT resource allows oneto investigate the variation of gesture-making patterns in conversations between sighted people and people with visualimpairment. After discussing the transcription methods and technical procedures employed in our study, we will propose aunified CoNLL-U corpus and indicate our future steps.

In this paper, we examine the competition between pairs of adjectives in Italian that are antonyms of the same term: one is a “morphological antonym” formed by negative prefixation, the other is a “lexical antonym” with no morphological relationship with the term in question. We consider pairs of adjectives that are reported as antonyms in lexicographic resources and extract the nouns that can be modified by both adjectives from a large corpus. We select a set of 8 nouns for each pair that present higher, lower, and comparable frequencies combined with each antonym respectively and then we perform two experiments with a LLM. Firstly, we perform experiments for masked-token prediction of the adjective, to study the correlation between prediction accuracy and the frequency of the noun-antonym pair. Secondly, we perform a polarity-flip experiment with a multilingual LLM, asking to change the adjective into its positive counterpart, and study the cases where the antonym is changed to the morphological antonym’s lexical base, under the hypothesis that a flip to the lexical base indicates a narrower set of senses of the antonymic counterpart.

This paper contains a preliminary corpus study of oxymorons, a figure of speech so far under-investigated in NLP-oriented research. The study resulted in a list of 376 oxymorons, identified by extracting a set of antonymous pairs (under various configurations) from corpora of written Italian and by manually checking the results. A complementary method is also envisaged for discovering contextual oxymorons, which are highly relevant for the detection of humor, irony and sarcasm.