Natural Language Interface System for Querying Wikidata
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


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Research Paper | Computer Engineering | India | Volume 9 Issue 5, May 2020 | Popularity: 7.1 / 10


     

Natural Language Interface System for Querying Wikidata

Muhammad Reza Jafari, Dr. Vinod Kumar


Abstract: Nowadays, information has a huge impact in our daily life; hence its extraction from the web is a need for everyone. However, due to lack of knowledge of query languages, an end-user cannot extract information from knowledge bases as they should. Asking question in Natural Language from knowledge bases enable end-user to extract data from such knowledge sources in a more efficient and fast way. Wikidata is one of the biggest knowledge bases which extract data in a triple format from Wikipedia. Therefore this research project aims at designing and implementing Natural Language Interface system for querying Wikidata. To achieve this objective, a Natural Language Interface was designed using Wikidata in python for processing the input question of user and give some answer to user. Firstly, preprocessing of input query was done, which involved tokenization, Part of Speech (POS) Tagging, Stemming and Lemmatization, Name Entity Recognition (NER), Chunking, Synonym check for words taken using WordNet. Then, Question Classification and SPARQL were performed to minimize the search area, show the type of output, and display the answer to the user respectively. The results of the experiment showed that processing is much efficient based on response time.


Keywords: Natural Language Processing, Wikidata, Natural language Interface, Question Answering System


Edition: Volume 9 Issue 5, May 2020


Pages: 539 - 542



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Muhammad Reza Jafari, Dr. Vinod Kumar, "Natural Language Interface System for Querying Wikidata", International Journal of Science and Research (IJSR), Volume 9 Issue 5, May 2020, pp. 539-542, https://www.ijsr.net/getabstract.php?paperid=SR20506232010, DOI: https://www.doi.org/10.21275/SR20506232010

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