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        <title>Delexicalized transfer parsing for low-resource languages using transformed and combined treebanks</title>
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    <name type="personal">
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            <title>Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies</title>
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            <namePart type="given">Jan</namePart>
            <namePart type="family">Hajič</namePart>
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        <name type="personal">
            <namePart type="given">Dan</namePart>
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    <abstract>This paper describes our dependency parsing system in CoNLL-2017 shared task on Multilingual Parsing from Raw Text to Universal Dependencies. We primarily focus on the low-resource languages (surprise languages). We have developed a framework to combine multiple treebanks to train parsers for low resource languages by delexicalization method. We have applied transformation on source language treebanks based on syntactic features of the low-resource language to improve performance of the parser. In the official evaluation, our system achieves an macro-averaged LAS score of 67.61 and 37.16 on the entire blind test data and the surprise language test data respectively.</abstract>
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    <identifier type="doi">10.18653/v1/K17-3019</identifier>
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%0 Conference Proceedings
%T Delexicalized transfer parsing for low-resource languages using transformed and combined treebanks
%A Das, Ayan
%A Zaffar, Affan
%A Sarkar, Sudeshna
%Y Hajič, Jan
%Y Zeman, Dan
%S Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies
%D 2017
%8 August
%I Association for Computational Linguistics
%C Vancouver, Canada
%F das-etal-2017-delexicalized
%X This paper describes our dependency parsing system in CoNLL-2017 shared task on Multilingual Parsing from Raw Text to Universal Dependencies. We primarily focus on the low-resource languages (surprise languages). We have developed a framework to combine multiple treebanks to train parsers for low resource languages by delexicalization method. We have applied transformation on source language treebanks based on syntactic features of the low-resource language to improve performance of the parser. In the official evaluation, our system achieves an macro-averaged LAS score of 67.61 and 37.16 on the entire blind test data and the surprise language test data respectively.
%R 10.18653/v1/K17-3019
%U https://aclanthology.org/K17-3019
%U https://doi.org/10.18653/v1/K17-3019
%P 182-190

Markdown (Informal)

[Delexicalized transfer parsing for low-resource languages using transformed and combined treebanks](https://aclanthology.org/K17-3019) (Das et al., CoNLL 2017)

• Delexicalized transfer parsing for low-resource languages using transformed and combined treebanks (Das et al., CoNLL 2017)

ACL

• Ayan Das, Affan Zaffar, and Sudeshna Sarkar. 2017. Delexicalized transfer parsing for low-resource languages using transformed and combined treebanks. In Proceedings of the CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, pages 182–190, Vancouver, Canada. Association for Computational Linguistics.