Paper Info
Title
The Galactic Dependencies Treebanks: Getting More Data by Synthesizing New Languages.
Abstract
We release Galactic Dependencies 1.0—a large set of synthetic languages not found on Earth, but annotated in Universal Dependencies format. This new resource aims to provide training and development data for NLP methods that aim to adapt to unfamiliar languages. Each synthetic treebank is produced from a real treebank by stochastically permuting the dependents of nouns and/or verbs to match the word order of other real languages. We discuss the usefulness, realism, parsability, perplexity, and diversity of the synthetic languages. As a simple demonstration of the use of Galactic Dependencies, we consider single-source transfer, which attempts to parse a real target language using a parser trained on a “nearby” source language. We find that including synthetic source languages somewhat increases the diversity of the source pool, which significantly improves results for most target languages.
Year
DOI
Venue
2016
10.1162/tacl_a_00113
Trans. Assoc. Comput. Linguistics
Field
DocType
Volume
Perplexity,Word order,Computer science,Noun,Universal dependencies,Permutation,Synthetic language,Natural language processing,Treebank,Artificial intelligence,Parsing
Journal
4
Issue
ISSN
Citations 
1
Transactions of the Association of Computational Linguistics (TACL), 4:491--505, 2016
3
PageRank 
References 
Authors
0.37
17
2
Name
Order
Citations
PageRank
Dingquan Wang1112.51
Jason Eisner21825173.00