Knowledge bases and description logics applications to natural language texts analysis

H.I. Hoherchak

Abstract


The article describes some ways of knowledge bases application to natural language texts analysis and solving some of their processing tasks. The basic problems of natural language processing are considered, which are the basis for their semantic analysis: problems of tokenization, parts of speech tagging, dependency parsing, correference resolution. The basic concepts of knowledge bases theory are presented and the approach to their filling based on Universal Dependencies framework and the correference resolution problem is proposed. Examples of applications for knowledge bases filled with natural language texts in practical problems are given, including checking constructed syntactic and semantic models for consistency and question answering.

Problems in programming 2020; 2-3: 259-269


Keywords


knowledge bases; natural language processing; syntax dependencies; coreference resolution; semantic analysis

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References


Stanovsky G., Dagan I. Creating a Large Benchmark for Open Information Extraction. Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing. Austin, Texas, US. 2016. P. 2300–2305.

Cetto M., Niklaus C., Freitas A., Handschuh S. Graphene: A Context-Preserving Open Information Extraction System. Proceedings of the 27th International Conference on Computational Linguistics: System Demonstrations. Santa Fe, New Mexico. 2018. P. 94–98.

Zhan J., Zhao H. Span Based Open Information Extraction. 2019.

Léchelle W., Gotti F., Langlais P. WiRe57: A Fine-Grained Benchmark for Open Information Extraction. 2019. P. 6–15.

Niklaus C., Cetto M., Freitas A., Handschuh S. A Survey on Open Information Extraction. Proceedings of the 27th International Conference on Computational Linguistics. Santa Fe, New Mexico, USA. 2018. P. 3866–3878.

Manning C., Grow T., Grenager T., Finkel J., Bauer J. Stanford Tokenizer. 2002.

McDonald R., Nivre J., Quirmbach-Brundage Y., Goldberg Y., Das D., Ganchev K., Hall K., Petrov S., Zhang H., Täckström O., Bedini C., Castelló N.B. and Lee J. Universal Dependency Annotation for Multilingual Parsing. In Proceedings of ACL. 2003. P. 92–97.

Bohnet B., McDonald R., Simões G., Andor D., Pitler E. and Maynez J. Morphosyntactic Tagging with a Meta-BiLSTM Model over Context Sensitive Token Encodings. Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics. 2018. P. 2642–2652.

Mrini K., Dernoncourt F., Bui T., Chang W. and Nakashole N. Rethinking Self-Attention: An Interpretable Self-Attentive Encoder-Decoder Parser. 2019.

Darchuk N. Automated syntax analysis of texts from Ukrainian language corpus. Ukrainian linguistics. 2013. N 43. P. 11–19. (In Ukrainian)

Devlin J., Chang M.-W., Lee K. and Toutanova K. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding. NAACL-HLT. 2019. P. 4171–4186.

Baader F., Calvanese D., McGuinness D., Nardi D. and Patel-Schneider P. The Description Logic Handbook. Cambridge University Press. 2007. P. 578.

Serhiienko I., Kryvyi S., Provotar O. Algebraic aspects of information technology. Scientific thought. 2011. 399 p. (In Ukrainian)

Kryvyi S., Darchuk N., Provotar O. Onlogoly-based systems of natural language analysis. Problems of programming. 2018. N 2-3. P. 132–139. (In Ukrainian)

Kryvyi S., Darchuk N., Yasenova I., Holovina O., Soliar A. Methods and means of knowledge representation systems. – Publisher: ITHEA. – Inter. journ. «Information Content and Processing». 2017. Vol. 4. N 1. P. 62–99. (In Russian)

Palagin O., Kryvyi S., Petrenko N.. Knowledge-oriented information systems with the processing of natural language objects: the basis of ethodology, architectural and structural organization. Control Systems and Computers. 2009. N 3. P. 42–55. (In Russian)

Palagin O., Kryvyi S., Petrenko N. On the automation of the process of extracting knowledge from natural language texts. Natural and Artificial Intelligence Intern. Book Series. Inteligent Processing. ITHEA. Sofia. N 9. 2012. P. 44–52. (In Russian)

Palagin O., Kryvyi S., Bibikov D.. Processing natural language sentences using dictionaries and words frequency. Natural and Artificial Intelligence Intern. Book Series. Inteligent Processing. ITHEA. Sofia. N 9. 2010. P. 44–52. (In Russian)


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