German and French Neural Supertagging Experiments for LTAG Parsing

Tatiana Bladier, Andreas van Cranenburgh, Younes Samih, Laura Kallmeyer


Abstract
We present ongoing work on data-driven parsing of German and French with Lexicalized Tree Adjoining Grammars. We use a supertagging approach combined with deep learning. We show the challenges of extracting LTAG supertags from the French Treebank, introduce the use of left- and right-sister-adjunction, present a neural architecture for the supertagger, and report experiments of n-best supertagging for French and German.
Anthology ID:
P18-3009
Volume:
Proceedings of ACL 2018, Student Research Workshop
Month:
July
Year:
2018
Address:
Melbourne, Australia
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
59–66
Language:
URL:
https://www.aclweb.org/anthology/P18-3009
DOI:
10.18653/v1/P18-3009
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PDF:
http://aclanthology.lst.uni-saarland.de/P18-3009.pdf