{"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/biomedical-event-trigger-identification-using","title":"Biomedical Event Trigger Identification Using Bidirectional Recurrent Neural Network Based Models","arxiv_id":"1705.09516","date":"2017-05-26","proceeding":"WS 2017 8","authors":["Patchigolla V S S Rahul","Sunil Kumar Sahu","Ashish Anand"],"abstract":"Biomedical events describe complex interactions between various biomedical\nentities. Event trigger is a word or a phrase which typically signifies the\noccurrence of an event. Event trigger identification is an important first step\nin all event extraction methods. However many of the current approaches either\nrely on complex hand-crafted features or consider features only within a\nwindow. In this paper we propose a method that takes the advantage of recurrent\nneural network (RNN) to extract higher level features present across the\nsentence. Thus hidden state representation of RNN along with word and entity\ntype embedding as features avoid relying on the complex hand-crafted features\ngenerated using various NLP toolkits. Our experiments have shown to achieve\nstate-of-art F1-score on Multi Level Event Extraction (MLEE) corpus. We have\nalso performed category-wise analysis of the result and discussed the\nimportance of various features in trigger identification task.","url_abs":"http://arxiv.org/abs/1705.09516v1","url_pdf":"http://arxiv.org/pdf/1705.09516v1.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":"biomedical-event-trigger-identification-using","repo_url":"https://github.com/rahulpatchigolla/EventTriggerDetection","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"event-extraction","task_name":"Event Extraction"},{"task_slug":"sentence","task_name":"Sentence"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}