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Towards Better UD Parsing: Deep Contextualized Word Embeddings, Ensemble, and Treebank Concatenation
This paper describes our system (HIT-SCIR) submitted to the CoNLL 2018 shared task on Multilingual Parsing from Raw Text to Universal Dependencies. We base our submission on Stanford's winning systemExpand
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A Neural Transition-Based Approach for Semantic Dependency Graph Parsing
Semantic dependency graph has been recently proposed as an extension of tree-structured syntactic or semantic representation for natural language sentences. It particularly features the structuralExpand
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The HIT-SCIR System for End-to-End Parsing of Universal Dependencies
This paper describes our system (HIT-SCIR) for the CoNLL 2017 shared task: Multilingual Parsing from Raw Text to Universal Dependencies. Our system includes three pipelined components: Expand
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From static to dynamic word representations: a survey
In the history of natural language processing (NLP) development, the representation of words has always been a significant research topic. In this survey, we provide a comprehensive typology of wordExpand
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Transition-Based Chinese Semantic Dependency Graph Parsing
Chinese semantic dependency graph is extended from semantic dependency tree, which uses directed acyclic graphs to capture richer latent semantics of sentences. In this paper, we propose twoExpand
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Deep Contextualized Word Embeddings for Universal Dependency Parsing
Deep contextualized word embeddings (Embeddings from Language Model, short for ELMo), as an emerging and effective replacement for the static word embeddings, have achieved success on a bunch of sy...