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Identify semantic relationships between words in a text using a graph representation.

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Greatest papers with code

N-LTP: A Open-source Neural Chinese Language Technology Platform with Pretrained Models

24 Sep 2020HIT-SCIR/ltp

In addition, knowledge distillation where the single-task model teaches the multi-task model is further introduced to encourage the multi-task model to surpass its single-task teacher.

CHINESE WORD SEGMENTATION DEPENDENCY PARSING KNOWLEDGE DISTILLATION LEXICAL ANALYSIS NAMED ENTITY RECOGNITION PART-OF-SPEECH TAGGING SEMANTIC DEPENDENCY PARSING SEMANTIC ROLE LABELING

Simpler but More Accurate Semantic Dependency Parsing

ACL 2018 yzhangcs/parser

While syntactic dependency annotations concentrate on the surface or functional structure of a sentence, semantic dependency annotations aim to capture between-word relationships that are more closely related to the meaning of a sentence, using graph-structured representations.

DEPENDENCY PARSING SEMANTIC DEPENDENCY PARSING

Learning Joint Semantic Parsers from Disjoint Data

NAACL 2018 Noahs-ARK/NeurboParser

We present a new approach to learning semantic parsers from multiple datasets, even when the target semantic formalisms are drastically different, and the underlying corpora do not overlap.

DEPENDENCY PARSING SEMANTIC DEPENDENCY PARSING

Deep Multitask Learning for Semantic Dependency Parsing

ACL 2017 Noahs-ARK/NeurboParser

We present a deep neural architecture that parses sentences into three semantic dependency graph formalisms.

DEPENDENCY PARSING SEMANTIC DEPENDENCY PARSING

Semi-Supervised Semantic Dependency Parsing Using CRF Autoencoders

ACL 2020 JZXXX/Semi-SDP

Semantic dependency parsing, which aims to find rich bi-lexical relationships, allows words to have multiple dependency heads, resulting in graph-structured representations.

DEPENDENCY PARSING SEMANTIC DEPENDENCY PARSING

Transition-based Semantic Dependency Parsing with Pointer Networks

27 May 2020danifg/SemanticPointer

Transition-based parsers implemented with Pointer Networks have become the new state of the art in dependency parsing, excelling in producing labelled syntactic trees and outperforming graph-based models in this task.

DEPENDENCY PARSING SEMANTIC DEPENDENCY PARSING WORD EMBEDDINGS

Backpropagating through Structured Argmax using a SPIGOT

ACL 2018 Noahs-ARK/SPIGOT

We introduce the structured projection of intermediate gradients optimization technique (SPIGOT), a new method for backpropagating through neural networks that include hard-decision structured predictions (e. g., parsing) in intermediate layers.

DEPENDENCY PARSING SEMANTIC DEPENDENCY PARSING SENTIMENT ANALYSIS