Rafay Rashed

Academic

Career

Verbatim text

Automated Knowledge Graph Construction 
for Large Document Collections 

Carrying out complex, rich contextualized searches from a large pile of documents is no trivial 
matter and if facilitated could be extremely beneficial to the digital humanities domain. Our final 
year project, based on the symbolic Artificial Intelligence (AI) field - Knowledge Graph (KG), is a 
collaboration with the Goethe University of Frankfurt which has provided us with expert 
annotations of a tafsir dataset in TEI/XML format to enable contextualized search with semantics 
from historic Islamic literature. Our final year project is divided into three major modules, ontology 
(a formal semantic data model) design and evaluation, automated knowledge graph generation 
where we had to convert the data with TEI/XML into RDF, and making a web portal to enable users 
to run structured queries on the KG. We have used Protégé (A tool to create a knowledge base) for 
the first module, Python and Owlready for the second module, and Django for the development of 
the web portal. 
Our web portal provides the following features: 
- 
SPARQL Endpoint (enables users to query a knowledge base via the SPARQL language) 
- 
Browsing of Tafsir Al-Tabari 
- 
Advance Search from Tafsir Al-Tabari 











Technology Used: 
Python, Protégé, GraphDB, Owlready,  
SPARQL, Django, JavaScript, HTML, CSS, XML 
Supervisor Name: 
Dr Amna Basharat 
Group Members:   
Rafay Rashed (I18 - 0549) 
Talha Ahmed (I18 - 0658) 
Zaid Saeed (I18 - 0506)