{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/natural-language-processing-for-information","title":"Natural Language Processing for Information Extraction","arxiv_id":"1807.02383","date":"2018-07-06","proceeding":null,"authors":["Sonit Singh"],"abstract":"With rise of digital age, there is an explosion of information in the form of\nnews, articles, social media, and so on. Much of this data lies in unstructured\nform and manually managing and effectively making use of it is tedious, boring\nand labor intensive. This explosion of information and need for more\nsophisticated and efficient information handling tools gives rise to\nInformation Extraction(IE) and Information Retrieval(IR) technology.\nInformation Extraction systems takes natural language text as input and\nproduces structured information specified by certain criteria, that is relevant\nto a particular application. Various sub-tasks of IE such as Named Entity\nRecognition, Coreference Resolution, Named Entity Linking, Relation Extraction,\nKnowledge Base reasoning forms the building blocks of various high end Natural\nLanguage Processing (NLP) tasks such as Machine Translation, Question-Answering\nSystem, Natural Language Understanding, Text Summarization and Digital\nAssistants like Siri, Cortana and Google Now. This paper introduces Information\nExtraction technology, its various sub-tasks, highlights state-of-the-art\nresearch in various IE subtasks, current challenges and future research\ndirections.","url_abs":"http://arxiv.org/abs/1807.02383v1","url_pdf":"http://arxiv.org/pdf/1807.02383v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"natural-language-processing-for-information","repo_url":"https://github.com/carrliitos/NLPInformationExtraction","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"articles","task_name":"Articles"},{"task_slug":"coreference-resolution","task_name":"Coreference Resolution"},{"task_slug":"entity-linking","task_name":"Entity Linking"},{"task_slug":"information-retrieval","task_name":"Information Retrieval"},{"task_slug":"machine-translation","task_name":"Machine Translation"},{"task_slug":"named-entity-recognition-1","task_name":"Named Entity Recognition"},{"task_slug":"named-entity-recognition-ner","task_name":"Named Entity Recognition (NER)"},{"task_slug":"natural-language-understanding","task_name":"Natural Language Understanding"},{"task_slug":"question-answering","task_name":"Question Answering"},{"task_slug":"relation-extraction","task_name":"Relation Extraction"},{"task_slug":"retrieval","task_name":"Retrieval"},{"task_slug":"text-summarization","task_name":"Text Summarization"},{"task_slug":"translation","task_name":"Translation"},{"task_slug":"coreference-resolution-1","task_name":"coreference-resolution"},{"task_slug":"named-entity-recognition","task_name":"named-entity-recognition"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1807.02383","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}