Miklós Sebők - Rebeka Kiss

Does the Language of the Prompt Matter? Exploring GenAI Response Differences by Query Language

The growing use of generative AI tools in research and professional contexts raises important questions about linguistic bias and consistency in model outputs. This short study explores whether the language of a prompt—specifically, English versus Hungarian—affects the content, tone, and legal precision of responses produced by a state-of-the-art

Prompt-based JSON to .xlsx Conversion: Turning Interview Metadata into a Structured Excel File

Interview metadata often arrives in semi-structured formats, making it difficult to analyse or integrate into standard research workflows. This short prompt-based approach shows how GenAI can transform a JSON file containing interview-related metadata into a clean, structured Excel (.xlsx) file—in seconds, without requiring any programming knowledge. The method enables

Generative AI in the Teacher’s Toolbox: Crafting an AI and Ethics Assignment Brief

University lecturers can improve curriculum planning by using GenAI to create detailed assignment briefs quickly and effectively. This blog introduces a custom prompt that guides GenAI in producing a ready-to-use "AI and Ethics" group presentation brief. It shows how it saves time, incorporates real ethical dilemmas, and suggests

How a GenAI Learning Assistant Enhances Targeted Exam Preparation: A Case Study of Active Recall

GenAI can be efficiently used as a learning assistant, as demonstrated by this case study. This GenAI prompt assists university students in preparing for exams by targeting a specific topic from their lecture notes. It extracts the relevant section and creates focused revision questions to support active recall and understanding.

Data Pre-processing with GenAI: Standardising Geographic Location Data in an Input CSV

Data pre-processing is a crucial but often tedious stage in research, particularly when standardising complex CSV datasets. This blog demonstrates how GenAI can systematically structure geographic location data directly from an input CSV file without coding. Our primary objective was to ensure consistent and accurate categorisation, preparing the data for

Classifying Financial Texts into Pre-defined Subdomains

Natural Language Processing (NLP) allows us to automatically analyse and categorise textual data. With the help of GenAI, even complex classification tasks can now be executed using just a well-designed prompt. In this post, we present a practical example where GenAI classifies financial-related sentences into domain-specific categories, showcasing how effective