Multitask Learning for Cross-Lingual Transfer of Broad-coverage Semantic Dependencies
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F20%3A10427007" target="_blank" >RIV/00216208:11320/20:10427007 - isvavai.cz</a>
Result on the web
<a href="https://www.aclweb.org/anthology/2020.emnlp-main.663" target="_blank" >https://www.aclweb.org/anthology/2020.emnlp-main.663</a>
DOI - Digital Object Identifier
—
Alternative languages
Result language
angličtina
Original language name
Multitask Learning for Cross-Lingual Transfer of Broad-coverage Semantic Dependencies
Original language description
We describe a method for developing broad-coverage semantic dependency parsers for languages for which no semantically annotated resource is available. We leverage a multitask learning framework coupled with annotation projection. We use syntactic parsing as the auxiliary task in our multitask setup. Our annotation projection experiments from English to Czech show that our multitask setup yields 3.1% (4.2%) improvement in labeled F1-score on in-domain (out-of-domain) test set compared to a single-task baseline.
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