Detecting ongoing events using contextual word and sentence embeddings
作者：
Highlights：
• The Ongoing Event Detection (OED) task is defined.
• A dataset for the task is made available, along with extensive documentation.
• Baselines for the task using classical and state-of-the-art techniques are reported.
• A proposed model that uses contextual word and sentence embeddings is presented.
• An extensive empirical evaluation is reported with several variations of the models.
摘要
•The Ongoing Event Detection (OED) task is defined.•A dataset for the task is made available, along with extensive documentation.•Baselines for the task using classical and state-of-the-art techniques are reported.•A proposed model that uses contextual word and sentence embeddings is presented.•An extensive empirical evaluation is reported with several variations of the models.
论文关键词：Ongoing Event Detection,Information Extraction,Contextual embeddings,BERT,RNN,CNN
论文评审过程：Received 2 March 2021, Revised 20 May 2022, Accepted 20 July 2022, Available online 25 July 2022, Version of Record 1 August 2022.
论文官网地址：https://doi.org/10.1016/j.eswa.2022.118257
