T4: Unsupervised Natural Language Parsing (Introductory Tutorial)

Kewei Tu, Yong Jiang, Wenjuan Han, Yanpeng Zhao

Live Session 1: Apr 20, Live Session 1: Apr 20 (07:00-08:00 UTC) [Join Zoom Meeting]
Live Session 2: Apr 20, Live Session 2: Apr 20 (13:00-14:00 UTC) [Join Zoom Meeting]
Abstract: Unsupervised parsing learns a syntactic parser from training sentences without parse tree annotations. Recently, there has been a resurgence of interest in unsupervised parsing, which can be attributed to the combination of two trends in the NLP community: a general trend towards unsupervised training or pre-training, and an emerging trend towards finding or modeling linguistic structures in neural models. In this tutorial, we will introduce to the general audience what unsupervised parsing does and how it can be useful for and beyond syntactic parsing. We will then provide a systematic overview of major classes of approaches to unsupervised parsing, namely generative and discriminative approaches, and analyze their relative strengths and weaknesses. We will cover both decade-old statistical approaches and more recent neural approaches to give the audience a sense of the historical and recent development of the field. We will also discuss emerging research topics such as BERT-based approaches and visually grounded learning.

Time Event Hosts
Apr 20, (07:00-08:00 UTC) Part 1 Kewei Tu, Yong Jiang, Wenjuan Han, Yanpeng Zhao
Apr 20, (13:00-14:00 UTC) Part 2
Information about the virtual format of this tutorial: This tutorial has a prerecorded talk on this page (see below) that you can watch anytime during the conference. It also has two live sessions that will be conducted on Zoom and will be livestreamed on this page. Additionally, it has a chat window that you can use to have discussions with the tutorial teachers and other attendees anytime during the conference.