Using Stanford CoreNLP Capabilities for Semantic Information Extraction from Textual Descriptions

Communications in Computer and Information Science 2020
Ērika Nazaruka, Jānis Osis, Viktorija Gribermane

Automated extraction of semantic information from textual descriptions can be implemented by processing results of application of Stanford CoreNLP tools. This paper presents a sequence of processing steps and initial results of their application for two examples of a description of system’s functionality. The processing steps allow identifying main functional characteristics of the system and its operational domain. Results obtained as a result of application of the steps are compared with data obtained as a result of analysis by a developer. Application of Stanford CoreNLP parsers in certain cases can produce errors and can influence results of further processing. The comparison of the two results sets showed that variability of language constructs in descriptions affects an amount of implicitly expressed knowledge. Nevertheless, results of this research can be used as a start point of automated text processing for creation of analysis models.

Keywords
Knowledge acquisition, Topological functioning model, Computation independent model
DOI
10.1007/978-3-030-40223-5_1
Hyperlink
https://link.springer.com/chapter/10.1007%2F978-3-030-40223-5_1

Nazaruka, Ē., Osis, J., Gribermane, V. Using Stanford CoreNLP Capabilities for Semantic Information Extraction from Textual Descriptions. In: Communications in Computer and Information Science, Greece, Heraklion, 4-5 May, 2019. Germany: Springer International Publishing, 2020, pp.1-21. ISBN 978-3-030-40223-5. Available from: doi:10.1007/978-3-030-40223-5_1

Publication language
English (en)