Morpho-syntactic parsing based on neural networks and corpus data

This article presents methods to construct procedure of morpho-syntactic parsing based on corpus dataset analyzes. It contains 1) the method to eliminate morphological ambiguities using existing morphological parsers and then converting the results of parsing into the format of the language corpus u...

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Published in2015 Artificial Intelligence and Natural Language and Information Extraction, Social Media and Web Search FRUCT Conference (AINL-ISMW FRUCT) pp. 89 - 95
Main Authors Rybka, Roman, Sboev, Alexander, Moloshnikov, Ivan, Gudovskikh, Dmitry
Format Conference Proceeding
LanguageEnglish
Published FRUCT 01.11.2015
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Summary:This article presents methods to construct procedure of morpho-syntactic parsing based on corpus dataset analyzes. It contains 1) the method to eliminate morphological ambiguities using existing morphological parsers and then converting the results of parsing into the format of the language corpus used; 2) a method of selecting parameters for syntactic parsing and assessment of the achievable accuracy of parsing, which can be provided by the data of the used corpus; 3) a method of parsing sentences on the basis of neural network algorithms and a selected set of parameters in the format of used corpus. The basis for this study are sentences with unambiguous morpho-syntactic marking from the Russian National Corpus.
DOI:10.1109/AINL-ISMW-FRUCT.2015.7382975