NLP Data Cleansing Based on Linguistic Ontology Constraints

Abstract

Abstract. Linked Data comprises of an unprecedented volume of structured data on the Web and is adopted from an increasing number of domains. However, the varying quality of published data forms a barrier for further adoption, especially for Linked Data consumers. In this paper, we extend a previously developed methodology of Linked Data quality assessment, which is inspired by test-driven software development. Specifically, we enrich it with ontological support and different levels of result reporting and describe how the method is applied in the Natural Language Processing (NLP) area. NLP is -compared to other domains, such as biology -a late Linked Data adopter. However, it has seen a steep rise of activity in the creation of data and ontologies. NLP data quality assessment has become an important need for NLP datasets. In our study, we analysed 11 datasets using the lemon and NIF vocabularies in 277 test cases and point out common quality issues.

Assessing and Refining Mappingsto RDF to Improve Dataset Quality

“…The two main components of our solution are: the rml (Section 3.2) that uses mapping definitions expressed in rdf, a prerequisite for uniform quality assessment and automated refinements, as we discussed above, and the rdfunit validation framework (Section 3.2) due to its associated test-case-based architecture [20]. A proof-of-concept implementation relies on the rmlvalidator which can be found at https://github.com/RMLio/RML-Validator.git.…”

“…The rdfunit ontology provides multiple result representations in different formats [20],including rdfbased serialisations (rut:ExtendedTestCaseResult result type). Therefore, its results are easily processed by an agent that can automatically add and delete triples or suggest actions to the data publisher.…”

Data Cleaning Utilizing Ontology Tool

“…Dimitris et. al., [14] uses an NLP based approach for data cleaning where it uses Linked Data for cleaning data. In 2005, Xin et.…”

Knowledge Base Creation, Enrichment and Repair

“…RDFUnit [10][11][12] 17 is a framework for test-driven Linked Data quality assessment, which is inspired by test-driven software development. A key principle of test-driven software development is to start the development with the implementation of automated test-methods before the actual functionality is implemented.…”

“…Since different NER tools classify the entities with classes from different classification systems (classification ontologies), we perform alignment of those ontologies to the DBpedia Ontology 23 . In the future, we hope to exploit the availability of interoperable NIF corpora as described in [10].…”