Syntactic and semantic parsing has been investigated for decades, which is one primary
topic in the natural language processing community. This article aims for a brief survey on …

Convolutional Neural Network (CNN) has gained attractions in image analytics and speech
recognition in recent years. However, employing CNN for classification of graphs remains to …

In the last few years, convolutional neural networks (CNNs), along with recurrent neural
networks (RNNs), have become a basic building block in constructing complex deep …

We present neural network-based joint models for Chinese word segmentation, POS
tagging and dependency parsing. Our models are the first neural approaches for fully joint …

In this paper, we study the task of graph-based constituent parsing in the setting that
binarization is not conducted as a pre-processing step, where a constituent tree may consist …

关系抽取是自然语言处理的重要研究内容, 短语成分结构则是学界普遍认为能对关系抽取有重要
影响的特征信息. 然而目前短语成分应用于关系抽取任务时没有明显效果. 这主要有两个原因 …

Extracting bio-entity relations has emerged as an important task due to the ever-growing
number of bio-medical documents. In this paper, we present a simple and novel …

Syntactic parsing is an important topic in the field of Mongolian language information
processing. Compared with English and Chinese dependency parsing, Mongolian …

A two-layer labeling-based dependency analysis model is proposed to introduce the
location features of words for the coreference disambiguation of entities. Firstly, two layers of …

This article introduces a novel neural network framework for the approximate bilinear
algorithm that scales asymptotically with the input size. The network actually learns from the …