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        <title>Turku Neural Parser Pipeline: An End-to-End System for the CoNLL 2018 Shared Task</title>
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    <name type="personal">
        <namePart type="given">Jenna</namePart>
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        <namePart type="given">Filip</namePart>
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    <name type="personal">
        <namePart type="given">Niko</namePart>
        <namePart type="family">Miekka</namePart>
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    <name type="personal">
        <namePart type="given">Akseli</namePart>
        <namePart type="family">Leino</namePart>
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    <name type="personal">
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            <title>Proceedings of the CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies</title>
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            <namePart type="given">Daniel</namePart>
            <namePart type="family">Zeman</namePart>
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            <namePart type="given">Jan</namePart>
            <namePart type="family">Hajič</namePart>
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    <abstract>In this paper we describe the TurkuNLP entry at the CoNLL 2018 Shared Task on Multilingual Parsing from Raw Text to Universal Dependencies. Compared to the last year, this year the shared task includes two new main metrics to measure the morphological tagging and lemmatization accuracies in addition to syntactic trees. Basing our motivation into these new metrics, we developed an end-to-end parsing pipeline especially focusing on developing a novel and state-of-the-art component for lemmatization. Our system reached the highest aggregate ranking on three main metrics out of 26 teams by achieving 1st place on metric involving lemmatization, and 2nd on both morphological tagging and parsing.</abstract>
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    <identifier type="doi">10.18653/v1/K18-2013</identifier>
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%0 Conference Proceedings
%T Turku Neural Parser Pipeline: An End-to-End System for the CoNLL 2018 Shared Task
%A Kanerva, Jenna
%A Ginter, Filip
%A Miekka, Niko
%A Leino, Akseli
%A Salakoski, Tapio
%Y Zeman, Daniel
%Y Hajič, Jan
%S Proceedings of the CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies
%D 2018
%8 October
%I Association for Computational Linguistics
%C Brussels, Belgium
%F kanerva-etal-2018-turku
%X In this paper we describe the TurkuNLP entry at the CoNLL 2018 Shared Task on Multilingual Parsing from Raw Text to Universal Dependencies. Compared to the last year, this year the shared task includes two new main metrics to measure the morphological tagging and lemmatization accuracies in addition to syntactic trees. Basing our motivation into these new metrics, we developed an end-to-end parsing pipeline especially focusing on developing a novel and state-of-the-art component for lemmatization. Our system reached the highest aggregate ranking on three main metrics out of 26 teams by achieving 1st place on metric involving lemmatization, and 2nd on both morphological tagging and parsing.
%R 10.18653/v1/K18-2013
%U https://aclanthology.org/K18-2013
%U https://doi.org/10.18653/v1/K18-2013
%P 133-142

Markdown (Informal)

[Turku Neural Parser Pipeline: An End-to-End System for the CoNLL 2018 Shared Task](https://aclanthology.org/K18-2013) (Kanerva et al., CoNLL 2018)

• Turku Neural Parser Pipeline: An End-to-End System for the CoNLL 2018 Shared Task (Kanerva et al., CoNLL 2018)

ACL

• Jenna Kanerva, Filip Ginter, Niko Miekka, Akseli Leino, and Tapio Salakoski. 2018. Turku Neural Parser Pipeline: An End-to-End System for the CoNLL 2018 Shared Task. In Proceedings of the CoNLL 2018 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies, pages 133–142, Brussels, Belgium. Association for Computational Linguistics.