{"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/parser-extraction-of-triples-in-unstructured","title":"Parser Extraction of Triples in Unstructured Text","arxiv_id":"1811.05768","date":"2018-11-06","proceeding":null,"authors":["Shaun D'Souza"],"abstract":"The web contains vast repositories of unstructured text. We investigate the\nopportunity for building a knowledge graph from these text sources. We generate\na set of triples which can be used in knowledge gathering and integration. We\ndefine the architecture of a language compiler for processing\nsubject-predicate-object triples using the OpenNLP parser. We implement a\ndepth-first search traversal on the POS tagged syntactic tree appending\npredicate and object information. A parser enables higher precision and higher\nrecall extractions of syntactic relationships across conjunction boundaries. We\nare able to extract 2-2.5 times the correct extractions of ReVerb. The\nextractions are used in a variety of semantic web applications and question\nanswering. We verify extraction of 50,000 triples on the ClueWeb dataset.","url_abs":"http://arxiv.org/abs/1811.05768v1","url_pdf":"http://arxiv.org/pdf/1811.05768v1.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":"parser-extraction-of-triples-in-unstructured","repo_url":"https://github.com/shaundsouza/parser-triples","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"object","task_name":"Object"},{"task_slug":"pos","task_name":"POS"},{"task_slug":"question-answering","task_name":"Question Answering"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}