Engenharia de prompts para respostas de restaurantes em português: avaliação de tom, empatia, fluência e consistência de marca com LLMs
| dc.contributor.advisor | Melo, Tiago Eugenio de | |
| dc.contributor.advisor-lattes | http://lattes.cnpq.br/9912454472927669 | |
| dc.contributor.author | Silva, Danilo Bruno da | |
| dc.contributor.author-lattes | http://lattes.cnpq.br/4813617274613597 | |
| dc.contributor.referee1 | Melo, Tiago Eugenio de | |
| dc.contributor.referee1Lattes | http://lattes.cnpq.br/9912454472927669 | |
| dc.contributor.referee2 | Pontes, Danielle Pompeu Noronha | |
| dc.contributor.referee2Lattes | http://lattes.cnpq.br/0735042255042649 | |
| dc.contributor.referee3 | Figueiredo, Carlos Mauricio Serodio | |
| dc.contributor.referee3Lattes | http://lattes.cnpq.br/9060002746939878 | |
| dc.date.accessioned | 2026-09-14T18:26:25Z | |
| dc.date.issued | 2026-09-19 | |
| dc.description.abstract | Automating responses to online restaurant reviews requires balancing tone, empathy, fluency, and brand consistency, dimensions still underexplored for large language models (LLMs) applied to Brazilian Portuguese. This work evaluates the viability and maturity of three LLMs (GPT-5.5, Gemini 3.1, and Llama 4) for this task. Drawing on a corpus of 200 real reviews, partitioned into two temporal periods (pre- and post-LLM popularization), a factorial experiment was conducted crossing models, brand personas (formal and informal), and prompt engineering strategies (zero-shot and few-shot). The evaluation followed a mixed-methods design, combining Likert-scale judgments from 15 independent human raters with multidimensional automatic metrics: perplexity (fluency), ToneCal (tone adequacy), stylometric similarity (brand consistency), and the WASSA model (perceived empathy). Results show that no model is universally superior: Llama 4 leads in empathy and tone adequacy, while GPT-5.5 prevails in fluency and brand consistency, with statistically significant differences across models. The zero-shot strategy, supported by well-defined personas, tends to outperform few-shot in pragmatic dimensions. A directional inversion of the persona effect, informal preferred by human raters, yet formal favored by automatic metrics, reveals a systematic bias of computational proxies toward formal register. The main contribution is a multidimensional evaluation framework for text generation in Brazilian Portuguese, with results suggesting that triangulation between human and automatic evaluation is advisable for more robust conclusions in the evaluated scenario. | |
| dc.description.resumo | A gestão automatizada de avaliações online no setor gastronômico exige respostas que conciliem tom, empatia, fluência e consistência de marca, dimensões ainda pouco exploradas em modelos de linguagem de larga escala (LLMs) aplicados ao português brasileiro. Este trabalho avalia a viabilidade e a maturidade de três LLMs (GPT-5.5, Gemini 3.1 e Llama 4) para essa tarefa. A partir de um corpus de 200 comentários reais, segmentado em dois períodos (pré e pós-popularização das LLMs), conduziu-se um experimento fatorial cruzando modelos, personas de marca (formal e informal) e estratégias de engenharia de prompt (zero-shot e few-shot). A avaliação seguiu metodologia mista, combinando o julgamento de 15 avaliadores humanos em escala Likert com métricas automáticas multidimensionais: perplexidade (fluência), ToneCal (adequação de tom), similaridade estilométrica (consistência de marca) e modelo WASSA (empatia per cebida). Os resultados indicam que nenhum modelo é universalmente superior: o Llama 4 lidera em empatia e adequação de tom, enquanto o GPT-5.5 prevalece em fluência e consistência de marca, com diferenças estatisticamente significativas entre modelos. A es tratégia zero-shot, apoiada em descrições robustas de persona, tende a superar a few-shot nas dimensões pragmáticas. A inversão direcional do efeito de persona, informal preferida pelos avaliadores humanos, porém formal favorecida pelas métricas automáticas, eviden cia um viés sistemático dos proxies computacionais para o registro formal. A principal contribuição é a proposta de um framework de avaliação multidimensional para geração de texto em português brasileiro, cujos resultados sugerem que a triangulação entre avaliação humana e automática é desejável para conclusões mais robustas no cenário avaliado. | |
| dc.identifier.citation | SILVA, Danilo Bruno da. Engenharia de prompts para respostas de restaurantes em português: avaliação de tom, empatia, fluência e consistência de marca com LLMs. Manaus, 2026. 94f. TCC- (Graduação em engenharia de Computação) –Universidade do Estado do Amazonas. Escola Superior de Tecnologia. | |
| dc.identifier.uri | https://ri.uea.edu.br/handle/riuea/8623 | |
| dc.publisher | Universidade do Estado do Amazonas | |
| dc.publisher.initials | UEA | |
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| dc.rights | Attribution-NonCommercial-NoDerivs 3.0 United States | en |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/3.0/us/ | |
| dc.subject | Engenharia de Prompt | |
| dc.subject | Modelos de linguagem em Larga Escala (LLMs) | |
| dc.subject | Processamento de linguagem natural (PLN) | |
| dc.subject | Avaliação multidimensional | |
| dc.subject | Automação. | |
| dc.title | Engenharia de prompts para respostas de restaurantes em português: avaliação de tom, empatia, fluência e consistência de marca com LLMs | |
| dc.title.alternative | Prompt Engineering for Restaurant Responses in Portuguese: Evaluating Tone, Empathy, Fluency, and Brand Consistency with LLMs | |
| dc.type | Trabalho de Conclusão de Curso |
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