04/07/2020

Tetra-Tagging: Word-Synchronous Parsing with Linear-Time Inference

Nikita Kitaev, Dan Klein

Keywords: Tetra-Tagging, Word-Synchronous Parsing, Linear-Time Inference, constituency algorithm

Abstract Paper Similar Papers

Abstract: We present a constituency parsing algorithm that, like a supertagger, works by assigning labels to each word in a sentence. In order to maximally leverage current neural architectures, the model scores each word's tags in parallel, with minimal task-specific structure. After scoring, a left-to-right reconciliation phase extracts a tree in (empirically) linear time. Our parser achieves 95.4 F1 on the WSJ test set while also achieving substantial speedups compared to current state-of-the-art parsers with comparable accuracies.

 0
 0
 0
 0
  Share    
This is an embedded video. Talk and the respective paper are published at ACL 2020 virtual conference. If you are one of the authors of the paper and want to manage your upload, see the question "My papertalk has been externally embedded..." in the FAQ section.

Comments

Post Comment
no comments yet
code of conduct: tbd Characters remaining: 140

Similar Papers

 0
 0
 0
 0
 14:38 
 0
 0
 0
 0
 7:40 
 0
 0
 0
 0
 3:24 
 0
 0
 0
 0
 12:44 
 0
 0
 0
 0
 3:19 
 0
 0
 0
 0
 16:10 
 0
 0
 0
 0
 6:47 
 0
 0
 0
 0
 6:53 
 0
 0
 0
 0
 11:39 
 0
 0
 0
 1
 12:12 
 0
 0
 0
 0
 13:53 
 0
 0
 0
 0
 18:47 
 0
 0
 0
 0
 10:30 
 0
 0
 0
 0
 6:40 
 0
 0
 0
 0
 13:41 
 0
 0
 0
 0
 7:58 
 0
 0
 0
 0
 12:01 
 0
 0
 0
 0
 15:08 
 0
 0
 0
 0
 14:57 
 0
 0
 0
 0
 13:55 
 0
 0
 0
 0
 14:06 
 0
 0
 0
 0
 4:47 
 0
 0
 0
 0
 9:31 
 0
 0
 0
 0
 20:30 
 0
 0
 0
 0
 14:38 
 0
 0
 0
 0
 10:49 
 0
 0
 0
 0
 9:50 
 0
 0
 0
 0
 13:31 
 0
 0
 0
 0
 14:50 
 0
 0
 0
 0
 6:35 
 0
 0
 0
 0
 15:23 
 0
 0
 0
 0
 17:58 
 0
 0
 0
 0
 5:16 
 0
 0
 0
 0
 11:10 
 0
 0
 0
 0
 5:00 
 0
 0
 0
 0
 13:43 
 0
 0
 0
 0
 4:55 
 0
 0
 0
 0
 5:00 
 0
 0
 0
 0
 15:18 
 0
 0
 0
 0
 11:37