Computational linguistics and intelligent systems

Permanent URI for this communityhttps://ena.lpnu.ua/handle/ntb/39447

Browse

Has files: YesSubject: search.filters.subject.Information Extraction

Search Results

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    Unsupervised Open Relation Extraction
    (2021-05-04) Tarasenko, Yaroslav; Petrasova, Svitlana; National Technical University “Kharkiv Polytechnic Institute”
    The paper describes an approach to open relation extraction based on unsupervised machine learning. The state-of-the-art methods for extracting semantic relations are analyzed. The algorithm of automatic open relation extraction using statistical, syntactic and contextual information is proposed. The results of the study can be used in information retrieval, summarization, machine translation, question-answering systems, etc.
  • Thumbnail Image
    Item
    WikiWars-UA: Ukrainian corpus annotated with temporal expressions
    (Lviv Politechnic Publishing House, 2019-04-18) Grabar, Natalia; Hamon, Thierry; CNRS, Univ. Lille, UMR 81G3 - STL - Savoirs Textes Langage, F-59000 Lille, France; LIMSI, CNRS, Université Paris-Saclay. F-91405 Orsay, France; Université Paris 13. Sorbonne Paris Cité. F-93430 Villetaneuse. France
    Reliability of tools and reproducibility of study results are important features of modern Natural Language Processing (NLP) tools and methods. The scientific research is indeed increasingly coming under criticism for the lack of reproducibility of results. First step towards the reproducibility is related to the availability of freely usable tools and corpora. In our work, we are interested in automatic processing of unstructured documents for the extraction of temporal information. Our main objective is to create reference annotated corpus with temporal information related to dates (absolute and relative), periods, time, etc. in Ukrainian, and to their normalization. The approach relies on the adaptation of existing application, automatic pre-annotation of WikiWars corpus in Ukrainian and its manual correction. The reference corpus permits to reliably evaluate the current version of the automatic temporal annotator and to prepare future work on these topics.