Papers › Tagging and parsing of multidomain collections

Tagging and parsing of multidomain collections

17 Jun 2020Proceedings of the International Conference “Dialogue 2020” 2020 6archive 2025-07-28

Alexey Sorokin, Ivan Smurov, Denis Kirianov

In this paper we describe our submission to GramEval2020 competition on morphological tagging, lemmatization and dependency parsing. Our model uses biaffine attention over the BERT representations. The main feature of our work is the extensive usage of language model, tagger and parser fine-tuning on several distinct genres and the implementation of genre classifier. To deal with dataset idiosyncrasies we also extensively apply handwritten rules. Our model took second place in the overall model performance scoring 90.8 aggregate measure over all 4 tasks.

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Tasks

Dependency Parsing Language Modeling Language Modelling Lemmatization Morphological Tagging

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Methods

Adam Attention Attention Dropout BERT Dense Connections Dropout Layer Normalization Linear Layer Linear Warmup With Linear Decay Multi-Head Attention Residual Connection Softmax Weight Decay WordPiece

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