@inproceedings{szucs-etal-2025-recognizing,
    title = "Recognizing the Structure and Content of {H}ungarian Civil Registers",
    author = "Sz{\'{u}}cs, Kata {\'A}gnes  and
      Vad{\'a}sz, No{\'e}mi  and
      Z{\'a}ros, Zsolt B{\'e}la",
    editor = "Angelova, Galia  and
      Kunilovskaya, Maria  and
      Escribe, Marie  and
      Mitkov, Ruslan",
    booktitle = "Proceedings of the 15th International Conference on Recent Advances in Natural Language Processing - Natural Language Processing in the Generative AI Era",
    month = sep,
    year = "2025",
    address = "Varna, Bulgaria",
    publisher = "INCOMA Ltd., Shoumen, Bulgaria",
    url = "https://preview.aclanthology.org/corrections-2026-01/2025.ranlp-1.140/",
    pages = "1215--1223",
    abstract = "The study evaluates key steps in a system for processing data from digitized Hungarian state register records (1895-1980) into an SQL database. It examines how template selection and post-processing impact data accessibility and integration. The research details the compiled datasets, annotation processes, and evaluation functions used to measure processing quality, emphasizing template selection and post-processing to improve the overall workflow and the accuracy of the published data. An evaluation method for publishing structured data provides a model for similar projects."
}