NDLI: Online Reasoning for Semantic Error Detection in Text

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Online Reasoning for Semantic Error Detection in Text

Content Provider	Springer Nature Link
Author	Dou, Dejing Gutierrez, Fernando Silva, Nisansa Fickas, Stephen
Copyright Year	2017
Abstract	Identifying incorrect content (i.e., semantic error) in text is a difficult task because of the ambiguous nature of written natural language and the many factors that can make a statement semantically erroneous. Current methods identify semantic errors in a sentence by determining whether it contradicts the domain to which the sentence belongs. However, because these methods are constructed on expected logic contradictions, they cannot handle new or unexpected semantic errors. In this paper, we propose a new method for detecting semantic errors that is based on logic reasoning. Our proposed method converts text into logic clauses, which are later analyzed against a domain ontology by an automatic reasoner to determine its consistency. This approach can provide a complete analysis of the text, since it can analyze a single sentence or sets of multiple sentences. When there are multiple sentences to analyze, in order to avoid the high complexity of reasoning over a large set of logic clauses, we propose rules that reduce the set of sentences to analyze, based on the logic relationships between sentences. In our evaluation, we have found that our proposed method can identify a significant percentage of semantic errors and, in the case of multiple sentences, it does so without significant computational cost. We have also found that both the quality of the information extraction output and modeling elements of the ontology (i.e., property domain and range) affect the capability of detecting errors.
Starting Page	139
Ending Page	153
Page Count	15
File Format	PDF
ISSN	18612032
Journal	Journal on Data Semantics
Volume Number	6
Issue Number	3
e-ISSN	18612040
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2017-07-05
Publisher Place	Berlin, Heidelberg
Access Restriction	Subscribed
Subject Keyword	Information Systems Applications (incl.Internet) Ontology Database Management Information Storage and Retrieval Artificial Intelligence (incl. Robotics) Semantic error detection Information extraction IT in Business
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Computer Networks and Communications Information Systems

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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