Informatics and Applications
2019, Volume 13, Issue 2, pp 83-91
COMPATIBILITY OF LOGICAL SEMANTIC RELATIONS: METHODS OF QUANTITATIVE ANALYSIS
- O. Yu. Inkova
- M. G. Kruzhkov
Abstract
The paper deals with logical semantic relations (LSR) that ensure text coherence and examines their explicit markers in text, i. e., connectives. An overview of existing approaches to definition and classification of LSRs is presented; different LSR combination patterns are examined. To make quantitative assessment of LSR compatibility, one should be able to annotate LSRs and their markers in texts. To support such annotation, a supracorpora database was developed, including customizable faceted classifications for LSRs and connectives.
Based on the database data, quantitative information on relations combinations was accumulated and interpreted.
For example, it was demonstrated that adjoining relations collocate with extensional generalization relations much more often than with relations of specifications; discourse realizations commonly used to mark more than one relation at a time were identified, etc. The results of LSR compatibility analysis were used to elaborate the methodology of reversible generalization of information objects. High flexibility and accessibility of the proposed approach allows researchers to address the underinvestigated problem of LSR compatibility.
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[+] About this article
Title
COMPATIBILITY OF LOGICAL SEMANTIC RELATIONS: METHODS OF QUANTITATIVE ANALYSIS
Journal
Informatics and Applications
2019, Volume 13, Issue 2, pp 83-91
Cover Date
2019-06-30
DOI
10.14357/19922264190212
Print ISSN
1992-2264
Publisher
Institute of Informatics Problems, Russian Academy of Sciences
Additional Links
Key words
databases; quantitative analysis; connectives; logical semantic relations; annotation of relations; generalization of information objects
Authors
O. Yu. Inkova
and M. G. Kruzhkov
Author Affiliations
Institute of Informatics Problems, Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russian Federation
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