From unstructured to structured : context based named entity mining from text With recent advances in the area of information extraction automatically extracting structured information from a vast amount of unstructured textual data becomes an important task which is infeasible for humans to capture all information manually. Named entities (e.g. persons organizations and locations) which are crucial components in texts are usually the subjects of structured information from textual documents. Therefore the task of named entity mining receives much attention. It consists of three major subtasks which are named entity recognition named entity linking and relation extraction. These three tasks build up an entire pipeline of a named entity mining system where each of them has its challenges and can be employed for further applications. As a fundamental task in the natural language processing domain studies on named entity recognition have a long history and many existing approaches produce reliable results. The task is aiming to extract mentions of named entities in text and identify their types. […]