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        <title>An Unsupervised Method for Uncovering Morphological Chains</title>
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    <name type="personal">
        <namePart type="given">Karthik</namePart>
        <namePart type="family">Narasimhan</namePart>
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    <name type="personal">
        <namePart type="given">Regina</namePart>
        <namePart type="family">Barzilay</namePart>
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    <name type="personal">
        <namePart type="given">Tommi</namePart>
        <namePart type="family">Jaakkola</namePart>
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    <abstract>Most state-of-the-art systems today produce morphological analysis based only on orthographic patterns. In contrast, we propose a model for unsupervised morphological analysis that integrates orthographic and semantic views of words. We model word formation in terms of morphological chains, from base words to the observed words, breaking the chains into parent-child relations. We use log-linear models with morpheme and word-level features to predict possible parents, including their modifications, for each word. The limited set of candidate parents for each word render contrastive estimation feasible. Our model consistently matches or outperforms five state-of-the-art systems on Arabic, English and Turkish.</abstract>
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    <identifier type="doi">10.1162/tacl_a_00130</identifier>
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        <url>https://aclanthology.org/Q15-1012</url>
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    <part>
        <date>2015</date>
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            <start>157</start>
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%0 Journal Article
%T An Unsupervised Method for Uncovering Morphological Chains
%A Narasimhan, Karthik
%A Barzilay, Regina
%A Jaakkola, Tommi
%J Transactions of the Association for Computational Linguistics
%D 2015
%V 3
%I MIT Press
%C Cambridge, MA
%F narasimhan-etal-2015-unsupervised
%X Most state-of-the-art systems today produce morphological analysis based only on orthographic patterns. In contrast, we propose a model for unsupervised morphological analysis that integrates orthographic and semantic views of words. We model word formation in terms of morphological chains, from base words to the observed words, breaking the chains into parent-child relations. We use log-linear models with morpheme and word-level features to predict possible parents, including their modifications, for each word. The limited set of candidate parents for each word render contrastive estimation feasible. Our model consistently matches or outperforms five state-of-the-art systems on Arabic, English and Turkish.
%R 10.1162/tacl_a_00130
%U https://aclanthology.org/Q15-1012
%U https://doi.org/10.1162/tacl_a_00130
%P 157-167

Markdown (Informal)

[An Unsupervised Method for Uncovering Morphological Chains](https://aclanthology.org/Q15-1012) (Narasimhan et al., TACL 2015)

• An Unsupervised Method for Uncovering Morphological Chains (Narasimhan et al., TACL 2015)

ACL

• Karthik Narasimhan, Regina Barzilay, and Tommi Jaakkola. 2015. An Unsupervised Method for Uncovering Morphological Chains. Transactions of the Association for Computational Linguistics, 3:157–167.