HHMM at SemEval-2019 Task 2: Unsupervised Frame Induction using Contextualized Word Embeddings
University of Hamburg（汉堡大学）；Skolkovo Institute of Science and Technology（斯科尔科沃科学技术研究所）；University of Mannheim（曼海姆大学）；Samsung R&D Institute Russia（三星俄罗斯研发中心）；Lomonosov Moscow State University（罗蒙诺索夫莫斯科国立大学）
英文摘要：
We present our system for semantic frame induction that showed the best performance in Subtask B.1 and finished as the runner-up in Subtask A of the SemEval 2019 Task 2 on unsupervised semantic frame induction (QasemiZadeh et al., 2019). Our approach separates this task into two independent steps: verb clustering using word and their context embeddings and role labeling by combining these embeddings with syntactical features. A simple combination of these steps shows very competitive results and can be extended to process other datasets and languages.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
