Logical-linguistic model for multilingual Open Information Extraction
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Дата
2020
DOI
doi.org/10.1080/23311916.2020.1714829
Науковий ступінь
Рівень дисертації
Шифр та назва спеціальності
Рада захисту
Установа захисту
Науковий керівник
Члени комітету
Видавець
Анотація
Open Information Extraction (OIE) is a modern strategy to extract the triplet of facts from Web-document collections. However, most part of the current OIE approaches is based on NLP techniques such as POS tagging and dependency parsing, which tools are accessible not to all languages. In this paper, we suggest the logical-linguistic model, which basic mathematical means are logical-algebraic equations of finite predicates algebra. These equations allow expressing a semantic role of the participant of a triplet of the fact (Subject-Predicate-Object) due to the relations of grammatical characteristics of words in the sentence. We propose the model that extracts the unlimited domain-independent number of facts from sentences of different languages. The use of our model allows extracting the facts from unstructured texts without requiring a pre-specified vocabulary, by identifying relations in phrases and associated arguments in arbitrary sentences of English, Kazakh, and Russian languages. We evaluate our approach on corpora of three languages based on English and Kazakh bilingual news websites. We achieve the precision of facts extraction over 87% for English corpus, over 82% for Russian corpus and 71% for Kazakh corpus.
Опис
Ключові слова
Open Information Extraction, fact extraction from unstructured texts, Kazakh bilingual news websites, criminal subject, logical-linguistic model, finite predicates algebra
Бібліографічний опис
Logical-linguistic model for multilingual Open Information Extraction [Electronic resource] / N. Khairova [et al.] // Cogent Engineering. – Electronic text data. – 2020. – Vol. 7, Iss. 1. – 16 p. – URL: https://www.tandfonline.com/doi/pdf/10.1080/23311916.2020.1714829?needAccess=true, free (accessed 11.12.2020).