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Universal Dependencies 2.1
TLDR
The annotation scheme is based on (universal) Stanford dependencies, Google universal part-of-speech tags, and the Interset interlingua for morphosyntactic tagsets for morpho-lingual tagsets.
How Language-Neutral is Multilingual BERT?
TLDR
This work shows that mBERT representations can be split into a language-specific component and a language -neutral component, and that the language-neutral component is sufficiently general in terms of modeling semantics to allow high-accuracy word-alignment and sentence retrieval but is not yet good enough for the more difficult task of MT quality estimation.
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Universal Dependencies 2.0 – CoNLL 2017 Shared Task Development and Test Data
TLDR
This release contains the test data used in the CoNLL 2017 shared task on parsing Universal Dependencies, and complements the UD 2.0 release with 18 new parallel test sets and 4 test sets in surprise languages.
KLcpos3 - a Language Similarity Measure for Delexicalized Parser Transfer
We present KLcpos3 , a language similarity measure based on Kullback-Leibler divergence of coarse part-of-speech tag trigram distributions in tagged corpora. It has been designed for multilingual…
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Two-step translation with grammatical post-processing
TLDR
It is proved that it is possible to improve the MT quality of majority of the systems participating in WMT shared task by making both automatic (BLEU) and manual evaluations.
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On the Language Neutrality of Pre-trained Multilingual Representations
TLDR
This work investigates the language-neutrality of multilingual contextual embeddings directly and with respect to lexical semantics and shows how to reach state-of-the-art accuracy on language identification and match the performance of statistical methods for word alignment of parallel sentences without using parallel data.
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Adaptation of machine translation for multilingual information retrieval in the medical domain
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HamleDT 2.0: Thirty Dependency Treebanks Stanfordized
TLDR
The stanfordization of HamleDT 2.0 is regarded as generally successful, although it admits several shortcomings, especially in the distinction between direct and indirect objects, that have to be addressed in future.
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Universal Dependencies 1.4
TLDR
The annotation scheme is based on (universal) Stanford dependencies, Google universal part-of-speech tags, and the Interset interlingua for morphosyntactic tagsets for morpho-lingual tagsets.
DEPFIX: A System for Automatic Correction of Czech MT Outputs
TLDR
An improved version of DEPFIX (Marecek et al., 2011), a system for automatic rule-based post-processing of English-to-Czech MT outputs designed to increase their fluency and is able to improve the quality of the state-of-the-art MT systems.
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