AIDArabic+ Named Entity Disambiguation for Arabic Text

Named Entity Disambiguation (NED) is the problem of mapping mentions of ambiguous names in a natural language text onto canonical entities such as people or places, registered in a knowledge base. Recent advances in this field enable semantically understanding content in different types of text. While the problem had been extensively studied for the English text, the support for other languages and, in particular, Arabic is still in its infancy. In addition, Arabic web content (e.g . in the social media) has been exponentially increasing over the last few years. Therefore, we see a great potential for endeavors that support entity-level analytics of these data. AIDArabic is the first work in the direction of using evidences from both English and Arabic Wikipedia to allow disambiguation of Arabic content to an automatically generated knowledge base from Wikipedia. The contributions of this thesis are threefold: 1) We introduce EDRAK resource as an automatic augmentation for AIDArabic’s entity catalog and disambiguation data components using information beyond manually crafted data in the Arabic Wikipedia. We build EDRAK by fusing external web resources and the output of machine translation and transliteration applied on the data extracted from the English Wikipedia. 2) We incorporate an Arabic-specific input pre-processing module into the disambiguation process to handle the complex features of Arabic text. 3) We automatically build a test corpus from other parallel English-Arabic corpus to overcome the absence of standard benchmarks for Arabic NED systems. We evaluated the data resource as well as the full pipeline using a mix of manual and automatic assessment. Our enrichment approaches in EDRAK are capable of expanding the disambiguation space from 143K entities, in the original AIDArabic, to 2.4M entities. Moreover, the full disambiguation process is able to map 94.7% of the mentions to non-null entities with a precision of 73%, compared to 87.2% non-null mapping with only 69% precision in the original AIDArabic. Acknowledgements . AJ. J £ @Q J» @YÔg é<Ë YÒmÌ'@ During this thesis, I have learned several essential research skills that, I believe, will shape my research career. Therefore, I would like to express my sincere gratitude to Prof.Gerhard Weikum for giving me the opportunity to work under his supervision in such a pioneering group, for facilitating the research and for his valuable advice throughout the thesis. I also would like to show my sincere gratitude and appreciation for my advisor Mohamed Amir for his continuous guidance and support on the professional and personal levels. I really appreciate his patience teaching me loads of essential research, communication and planning skills. I am extremely thankful for his generosity sharing his valuable expertise and time. Working with him was one of the richest experiences in my life. I wish to have the opportunity to work with him again in the future. I would like to thank Akram El-korashy, Mayank Goyal and Uzair Mahmoud for their useful feedback regarding the thesis writing. Also, our experiments would not be finalized without the help of the proactive volunteers who agreed to participate in our manual assessment. I would also like to thank the reviewers of this thesis for their precious time and effort. By the end of this masters program, I am grateful to the International MaxPlanck Research School for Computer Science (IMPRS-CS) family for their support throughout the master program. I believe, I was fortunate enough to be part of this big family. On the personal level, words will never be enough to express how I am thankful and indebted to my family (my parents, sister and brother) for their sincere support, encouragement and prayers throughout my life and my long education journey. I appreciate their patience towards my continuous absence. I would like to thank all my friends in Saarbrücken. I believe. I am blessed being surrounded by all those intelligent, caring and enthusiastic personalities. Finally, I would like to extend my sense of gratitude to everyone expressed his support and/or made Dua for me. Beijing, China. Mohamed Gad-Elrab July, 2015