  With rise of digital age, there is an explosion of information in the form of
news, articles, social media, and so on. Much of this data lies in unstructured
form and manually managing and effectively making use of it is tedious, boring
and labor intensive. This explosion of information and need for more
sophisticated and efficient information handling tools gives rise to
Information Extraction(IE) and Information Retrieval(IR) technology.
Information Extraction systems takes natural language text as input and
produces structured information specified by certain criteria, that is relevant
to a particular application. Various sub-tasks of IE such as Named Entity
Recognition, Coreference Resolution, Named Entity Linking, Relation Extraction,
Knowledge Base reasoning forms the building blocks of various high end Natural
Language Processing (NLP) tasks such as Machine Translation, Question-Answering
System, Natural Language Understanding, Text Summarization and Digital
Assistants like Siri, Cortana and Google Now. This paper introduces Information
Extraction technology, its various sub-tasks, highlights state-of-the-art
research in various IE subtasks, current challenges and future research
directions.
