End-to-end Multilingual Coreference Resolution with Mention Head Prediction
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F22%3A43965919" target="_blank" >RIV/49777513:23520/22:43965919 - isvavai.cz</a>
Result on the web
<a href="https://aclanthology.org/2022.crac-mcr.3/" target="_blank" >https://aclanthology.org/2022.crac-mcr.3/</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
End-to-end Multilingual Coreference Resolution with Mention Head Prediction
Original language description
This paper describes our approach to the CRAC 2022 Shared Task on Multilingual Coreference Resolution. Our model is based on a state-of-the-art end-to-end coreference resolution system. Apart from joined multilingual training, we improved our results with mention head prediction. We also tried to integrate dependency information into our model. Our system ended up in $3^{rd}$ place. Moreover, we reached the best performance on two datasets out of 13.
Czech name
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Czech description
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Classification
Type
O - Miscellaneous
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů