Este artigo investiga o modo como os adjetivos representam a experiência visual em descrições, em português brasileiro e em inglês, do conjunto de dados Framed Multi30K. Com base na Gramática Sistêmico-Funcional e na Semântica de Frames, o estudo classifica os adjetivos em Epítetos experienciais, Epítetos interpessoais e Classificadores, além de examinar os frames por eles evocados. Os resultados mostram que os Epítetos experienciais são predominantes, o que indica que os adjetivos são empregados principalmente para representar propriedades visualmente salientes. A anotação semântica também revela que Color é o frame mais frequente. Ao identificar os significados adjetivais mais salientes, o estudo contribui para compreender quais atributos visuais tendem a receber maior destaque por parte dos observadores.

This paper presents a multimodal semantic analysis of accessible Brazilian short films using a frame-based annotation approach. We introduce a subset of the Audition dataset, comprising six short films from the animation and documentary genres. We analysed three communicative modes: original audio, audio description, and visual content. Trained annotators semantically annotated each mode following the FrameNet Brazil multimodal methodology. To compare meaning across modalities, we used cosine similarity over frame-semantic representations. Results show that audio description aligns more closely with video content than original audio, reflecting its role in translating visual meaning into language. Our findings demonstrate the effectiveness of frame semantics in modelling meaning across modalities and provide quantitative evidence of audio description as a bridge between visual and verbal communication. The dataset and annotation strategies are a valuable resource for research on multimodal representation, semantic similarity, and accessible media.

This paper presents Lutma, a collaborative, semi-constrained, tutorial-based tool for contributing frames and lexical units to the Global FrameNet initiative. The tool parameterizes the process of frame creation, avoiding consistency violations and promoting the integration of frames contributed by the community with existing frames. Lutma is structured in a wizard-like fashion so as to provide users with text and video tutorials relevant for each step in the frame creation process. We argue that this tool will allow for a sensible expansion of FrameNet coverage in terms of both languages and cultural perspectives encoded by them, positioning frames as a viable alternative for representing perspective in language models.