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            <namePart type="given">Yuji</namePart>
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    <abstract>Parsing texts into universal dependencies (UD) in realistic scenarios requires infrastructure for the morphological analysis and disambiguation (MA&amp;D) of typologically different languages as a first tier. MA&amp;D is particularly challenging in morphologically rich languages (MRLs), where the ambiguous space-delimited tokens ought to be disambiguated with respect to their constituent morphemes, each morpheme carrying its own tag and a rich set features. Here we present a novel, language-agnostic, framework for MA&amp;D, based on a transition system with two variants — word-based and morpheme-based — and a dedicated transition to mitigate the biases of variable-length morpheme sequences. Our experiments on a Modern Hebrew case study show state of the art results, and we show that the morpheme-based MD consistently outperforms our word-based variant. We further illustrate the utility and multilingual coverage of our framework by morphologically analyzing and disambiguating the large set of languages in the UD treebanks.</abstract>
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%0 Conference Proceedings
%T Data-Driven Morphological Analysis and Disambiguation for Morphologically Rich Languages and Universal Dependencies
%A More, Amir
%A Tsarfaty, Reut
%Y Matsumoto, Yuji
%Y Prasad, Rashmi
%S Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
%D 2016
%8 December
%I The COLING 2016 Organizing Committee
%C Osaka, Japan
%F more-tsarfaty-2016-data
%X Parsing texts into universal dependencies (UD) in realistic scenarios requires infrastructure for the morphological analysis and disambiguation (MA&D) of typologically different languages as a first tier. MA&D is particularly challenging in morphologically rich languages (MRLs), where the ambiguous space-delimited tokens ought to be disambiguated with respect to their constituent morphemes, each morpheme carrying its own tag and a rich set features. Here we present a novel, language-agnostic, framework for MA&D, based on a transition system with two variants — word-based and morpheme-based — and a dedicated transition to mitigate the biases of variable-length morpheme sequences. Our experiments on a Modern Hebrew case study show state of the art results, and we show that the morpheme-based MD consistently outperforms our word-based variant. We further illustrate the utility and multilingual coverage of our framework by morphologically analyzing and disambiguating the large set of languages in the UD treebanks.
%U https://aclanthology.org/C16-1033
%P 337-348

Markdown (Informal)

[Data-Driven Morphological Analysis and Disambiguation for Morphologically Rich Languages and Universal Dependencies](https://aclanthology.org/C16-1033) (More & Tsarfaty, COLING 2016)

• Data-Driven Morphological Analysis and Disambiguation for Morphologically Rich Languages and Universal Dependencies (More & Tsarfaty, COLING 2016)

ACL

• Amir More and Reut Tsarfaty. 2016. Data-Driven Morphological Analysis and Disambiguation for Morphologically Rich Languages and Universal Dependencies. In Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers, pages 337–348, Osaka, Japan. The COLING 2016 Organizing Committee.