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

04/22/2019
by   Nikita Kitaev, et al.
0

We present a constituency parsing algorithm that maps from word-aligned contextualized feature vectors to parse trees. Our algorithm proceeds strictly left-to-right, processing one word at a time by assigning it a label from a small vocabulary. We show that, with mild assumptions, our inference procedure requires constant computation time per word. Our method gets 95.4 F1 on the WSJ test set.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
11/25/2020

Left Lyndon tree construction

We extend the left-to-right Lyndon factorisation of a word to the left L...
research
11/20/2019

Global Greedy Dependency Parsing

Most syntactic dependency parsing models may fall into one of two catego...
research
05/25/2021

An explicit algorithm for normal forms in small overlap monoids

If 𝒫 = ⟨ A | R ⟩ is a monoid presentation, then the relation words in...
research
02/05/2020

Parsing as Pretraining

Recent analyses suggest that encoders pretrained for language modeling c...
research
11/03/2022

Joint Chinese Word Segmentation and Span-based Constituency Parsing

In constituency parsing, span-based decoding is an important direction. ...
research
10/04/2021

SPaR.txt, a cheap Shallow Parsing approach for Regulatory texts

Automated Compliance Checking (ACC) systems aim to semantically parse bu...
research
09/05/2017

Optimizing for Measure of Performance in Max-Margin Parsing

Many statistical learning problems in the area of natural language proce...

Please sign up or login with your details

Forgot password? Click here to reset