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Found 29 papers, 10 papers with code
A Lipid Rafts Theory of Alzheimer's Disease
Competition resolution crucially depends on the formation of membrane lipid rafts, which requires astrocyte-produced cholesterol.
UCCA's Foundational Layer: Annotation Guidelines v2.1
This is the annotation manual for Universal Conceptual Cognitive Annotation (UCCA; Abend and Rappoport, 2013), specifically the Foundational Layer.
Semantic Structural Decomposition for Neural Machine Translation
Building on recent advances in semantic parsing and text simplification, we investigate the use of semantic splitting of the source sentence as preprocessing for machine translation.
Preparing SNACS for Subjects and Objects
Research on adpositions and possessives in multiple languages has led to a small inventory of general-purpose meaning classes that disambiguate tokens.
Content Differences in Syntactic and Semantic Representation
Syntactic analysis plays an important role in semantic parsing, but the nature of this role remains a topic of ongoing debate.
Content Differences in Syntactic and Semantic Representations
Syntactic analysis plays an important role in semantic parsing, but the nature of this role remains a topic of ongoing debate.
SemEval-2019 Task 1: Cross-lingual Semantic Parsing with UCCA
We present the SemEval 2019 shared task on UCCA parsing in English, German and French, and discuss the participating systems and results.
BLEU is Not Suitable for the Evaluation of Text Simplification
BLEU is widely considered to be an informative metric for text-to-text generation, including Text Simplification (TS).
Simple and Effective Text Simplification Using Semantic and Neural Methods
Here we present a simple and efficient splitting algorithm based on an automatic semantic parser.
Ranked #19 on
Text Simplification
on TurkCorpus
Semantic Structural Evaluation for Text Simplification
Current measures for evaluating text simplification systems focus on evaluating lexical text aspects, neglecting its structural aspects.
Universal Dependency Parsing with a General Transition-Based DAG Parser
This paper presents our experiments with applying TUPA to the CoNLL 2018 UD shared task.
Computing Word Classes Using Spectral Clustering
Clustering a lexicon of words is a well-studied problem in natural language processing (NLP).
SemEval 2019 Shared Task: Cross-lingual Semantic Parsing with UCCA - Call for Participation
Given the success of recent semantic parsing shared tasks (on SDP and AMR), we expect the task to have a significant contribution to the advancement of UCCA parsing in particular, and semantic parsing in general.
Multitask Parsing Across Semantic Representations
The ability to consolidate information of different types is at the core of intelligence, and has tremendous practical value in allowing learning for one task to benefit from generalizations learned for others.
Ranked #3 on
UCCA Parsing
on SemEval 2019 Task 1
The State of the Art in Semantic Representation
Semantic representation is receiving growing attention in NLP in the past few years, and many proposals for semantic schemes (e. g., AMR, UCCA, GMB, UDS) have been put forth.
A Transition-Based Directed Acyclic Graph Parser for UCCA
We present the first parser for UCCA, a cross-linguistically applicable framework for semantic representation, which builds on extensive typological work and supports rapid annotation.
Ranked #4 on
UCCA Parsing
on SemEval 2019 Task 1
Automatic Selection of Context Configurations for Improved Class-Specific Word Representations
With our selected context configurations, we train on only 14% (A), 26. 2% (V), and 33. 6% (N) of all dependency-based contexts, resulting in a reduced training time.
Edge-Linear First-Order Dependency Parsing with Undirected Minimum Spanning Tree Inference
The run time complexity of state-of-the-art inference algorithms in graph-based dependency parsing is super-linear in the number of input words (n).
