Efficient EUD Parsing
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F20%3A10427022" target="_blank" >RIV/00216208:11320/20:10427022 - isvavai.cz</a>
Result on the web
<a href="https://www.aclweb.org/anthology/2020.iwpt-1.20" target="_blank" >https://www.aclweb.org/anthology/2020.iwpt-1.20</a>
DOI - Digital Object Identifier
—
Alternative languages
Result language
angličtina
Original language name
Efficient EUD Parsing
Original language description
We present the system submission from the FASTPARSE team for the EUD Shared Task at IWPT 2020. We engaged with the task by focusing on efficiency. For this we considered training costs and inference efficiency. Our models are a combination of distilled neural dependency parsers and a rule-based system that projects UD trees into EUD graphs. We obtained an average ELAS of 74.04 for our official submission, ranking 4th overall.
Czech name
—
Czech description
—
Classification
Type
O - Miscellaneous
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
—
Continuities
—
Others
Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů