Semantic Dependency Parsing
14 papers with code • 3 benchmarks • 0 datasets
Identify semantic relationships between words in a text using a graph representation.
Latest papers
Auxiliary Tasks to Boost Biaffine Semantic Dependency Parsing
mcandito/aux-tasks-biaffine-graph-parser-findingsacl22
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Findings (ACL) 2022
The biaffine parser of Dozat and Manning (2017) was successfully extended to semantic dependency parsing (SDP) (Dozat and Manning, 2018).
A Higher-Order Semantic Dependency Parser
libinnlp/hosdp
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Higher-order features bring significant accuracy gains in semantic dependency parsing.
Automated Concatenation of Embeddings for Structured Prediction
Pretrained contextualized embeddings are powerful word representations for structured prediction tasks.
N-LTP: An Open-source Neural Language Technology Platform for Chinese
HIT-SCIR/ltp
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EMNLP (ACL) 2021
We introduce \texttt{N-LTP}, an open-source neural language technology platform supporting six fundamental Chinese NLP tasks: {lexical analysis} (Chinese word segmentation, part-of-speech tagging, and named entity recognition), {syntactic parsing} (dependency parsing), and {semantic parsing} (semantic dependency parsing and semantic role labeling).
Semi-Supervised Semantic Dependency Parsing Using CRF Autoencoders
Semantic dependency parsing, which aims to find rich bi-lexical relationships, allows words to have multiple dependency heads, resulting in graph-structured representations.
Transition-based Semantic Dependency Parsing with Pointer Networks
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.
Second-Order Semantic Dependency Parsing with End-to-End Neural Networks
Semantic dependency parsing aims to identify semantic relationships between words in a sentence that form a graph.
Multi-Task Semantic Dependency Parsing with Policy Gradient for Learning Easy-First Strategies
shuheikurita/semrl
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ACL 2019
In Semantic Dependency Parsing (SDP), semantic relations form directed acyclic graphs, rather than trees.
Simpler but More Accurate Semantic Dependency Parsing
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.
Backpropagating through Structured Argmax using a 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.
