@inproceedings{blinov-2020-semantic,
    title = "Semantic Triples Verbalization with Generative Pre-Training Model",
    author = "Blinov, Pavel",
    editor = "Castro Ferreira, Thiago  and
      Gardent, Claire  and
      Ilinykh, Nikolai  and
      van der Lee, Chris  and
      Mille, Simon  and
      Moussallem, Diego  and
      Shimorina, Anastasia",
    booktitle = "Proceedings of the 3rd International Workshop on Natural Language Generation from the Semantic Web (WebNLG+)",
    month = "12",
    year = "2020",
    address = "Dublin, Ireland (Virtual)",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/fix-sig-urls/2020.webnlg-1.17/",
    pages = "154--158",
    abstract = "The paper devoted to the problem of automatic text generation from RDF triples. This problem was formalized and proposed as a part of the 2020 WebNLG challenge. We describe our approach to the RDF-to-text generation task based on a neural network model with the Generative Pre-Training (GPT-2) architecture. In particular, we outline a way of base GPT-2 model conversion to a model with language and classification heads and discuss the text generation methods. To research the parameters' influence on the end-task performance a series of experiments was carried out. We report the result metrics and conclude with possible improvement directions."
}