Relation Extraction : A Survey
Sachin Pawar, Girish K. Palshikar, Pushpak Bhattacharyya

TL;DR
This survey reviews various supervised, semi-supervised, and unsupervised relation extraction techniques, including open information extraction and distant supervision, highlighting recent trends and future research directions in the field.
Contribution
It provides a comprehensive overview of relation extraction methods, their evolution, and potential future directions, serving as a resource for newcomers, researchers, and practitioners.
Findings
Summarizes key RE techniques and paradigms.
Highlights recent trends and advancements.
Suggests future research directions.
Abstract
With the advent of the Internet, large amount of digital text is generated everyday in the form of news articles, research publications, blogs, question answering forums and social media. It is important to develop techniques for extracting information automatically from these documents, as lot of important information is hidden within them. This extracted information can be used to improve access and management of knowledge hidden in large text corpora. Several applications such as Question Answering, Information Retrieval would benefit from this information. Entities like persons and organizations, form the most basic unit of the information. Occurrences of entities in a sentence are often linked through well-defined relations; e.g., occurrences of person and organization in a sentence may be linked through relations such as employed at. The task of Relation Extraction (RE) is to…
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Taxonomy
TopicsTopic Modeling · Natural Language Processing Techniques · Semantic Web and Ontologies
