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Paper Information

lrec2018-main-248

Ensemble Romanian Dependency Parsing with Neural Networks

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Title

Ensemble Romanian Dependency Parsing with Neural Networks

Abstract

SSPR (Semantics-driven Syntactic Parser for Romanian) is a neural network ensemble parser developed for Romanian (a Python 3.5 application based on the Microsoft Cognitive Toolkit 2.0 Python API) that combines the parsing decisions of a varying number (in our experiments, 3) of other parsers (MALT, RGB and MATE), using information from additional lexical, morpho-syntactic and semantic features. SSPR outperforms the best individual parser (MATE in our case) with 1.6% LAS points and it is in the same class with the top 5 Romanian performers at the CONLL 2017 dependency parsing shared task. The train and test sets were extracted from a Romanian dependency treebank we developed and validated in the Universal Dependencies format. The treebank, used in the CONLL 2017 Romanian track as well, is open licenced; the parser is available on request.


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