An Approach to a Linked Corpus Creation for a Literary Heritage Based on the Extraction of Entities from Texts

• Published in: Applied sciences Vol. 14; no. 2; p. 585
• Main Authors: Kassab, Kenan, Teslya, Nikolay
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01.01.2024
• Subjects: Bidirectional Encoder Representations from Transformers (BERT); Computational linguistics; Encyclopedias; Internet/Web search services; Knowledge; Language processing; Linguistics; Morphology; multilingual models; Multilingualism; Named Entity Recognition; Natural language interfaces; Natural language processing; Russian language; text processing; Writers; Russia
• ISSN: 2076-3417; 2076-3417
• DOI: 10.3390/app14020585

Working with the literary heritage of writers requires the studying of a large amount of materials. Finding them can take a considerable amount of time even when using search engines. The solution to this problem is to create a linked corpus of literary heritage. Texts in such a corpus will be united by common entities, which will make it possible to select texts not only by the occurrence of certain phrases in a query but also by common entities. To solve this problem, we propose the use of a Named Entity Recognition model trained on examples from a corpus of texts and a database structure for storing connections between texts. We propose to automate the process of creating a dataset for training a BERT-based NER model. Due to the specifics of the subject area, methods, techniques, and strategies are proposed to increase the accuracy of the model trained with a small set of examples. As a result, we created a dataset and a model trained on it which showed high accuracy in recognizing entities in the text (the average F1-score for all entity types is 0.8952). The database structure provides for the storage of unique entities and their relationships with texts and a selection of texts based on the entities. The method was tested for a corpus of texts from the literary heritage of Alexander Sergeevich Pushkin, which is also a difficult task due to the specifics of the Russian language.