Národní úložiště šedé literatury Nalezeno 1 záznamů.  Hledání trvalo 0.00 vteřin. 
Relation Extraction from Text
Královič, Kristián ; Ondřej, Karel (oponent) ; Smrž, Pavel (vedoucí práce)
This bachelor thesis focuses on the extraction of semantic relations between named entities in natural text using learning with a small number of supporting examples. The theoretical part of the thesis introduces methods for natural language representation using dense vectors and named entity recognition. Next, deep learning based approaches for semantic relation extraction are described. The theoretical part also includes a description of learning with a small number of training examples in the context of semantic relation extraction In the implementation part, a system for extracting semantic relations from text has been proposed. The system uses pairwise classifiers based on pre-trained language models like transformers to classify the relations. For the purpose of this work, the ELECTRA-PAIR, RoBERTa-PAIR and BERT-PAIR models were trained. In the experimental part of the thesis, these models are evaluated over different datasets. The experimental part also includes experiments aimed at classifying more complex semantic relations.

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