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One approach towards effective harnessing of this unstructured textual data could be its transformation into structured text. Hence, this study aims to present an overview of approaches that can be applied to extract key insights from textual data in a structured way. For this, Named Entity Recognition and Relation Extraction are being majorly addressed in this review study. The former deals with identification of named entities, and the latter deals with problem of extracting relation between set of entities. This study covers early approaches as well as the developments made up till now using machine learning models. Survey findings conclude that deep-learning-based hybrid and joint models are currently governing the state-of-the-art. It is also observed that annotated benchmark datasets for various textual-data generators such as Twitter and other social forums are not available. This scarcity of dataset has resulted into relatively less progress in these domains. Additionally, the majority of the state-of-the-art techniques are offline and computationally expensive. Last, with increasing focus on deep-learning frameworks, there is need to understand and explain the under-going processes in deep architectures.<\/jats:p>","DOI":"10.1145\/3445965","type":"journal-article","created":{"date-parts":[[2021,2,11]],"date-time":"2021-02-11T11:17:16Z","timestamp":1613042236000},"page":"1-39","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":223,"title":["Named Entity Recognition and Relation Extraction"],"prefix":"10.1145","volume":"54","author":[{"given":"Zara","family":"Nasar","sequence":"first","affiliation":[{"name":"PUCIT, University of the Punjab, Lahore, Lahore, Punjab, Pakistan"}]},{"given":"Syed Waqar","family":"Jaffry","sequence":"additional","affiliation":[{"name":"PUCIT, University of the Punjab, Lahore, Lahore, Punjab, Pakistan"}]},{"given":"Muhammad Kamran","family":"Malik","sequence":"additional","affiliation":[{"name":"PUCIT, University of the Punjab, Lahore, Lahore, Punjab, Pakistan"}]}],"member":"320","published-online":{"date-parts":[[2021,2,11]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Proceedings of the AAAI Workshop on Machine Learning for Information Extraction.","author":"Muslea I.","year":"1999"},{"key":"e_1_2_1_2_1","volume-title":"Proceedings of the INForum.","author":"Simoes G."},{"key":"e_1_2_1_3_1","unstructured":"Linguistic Data Consortium. 2017. 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