In Natural Language Processing (NLP), predicting linguistic structures, such as parsing and
chunking, has mostly relied on manual annotations of syntactic structures. This paper …

Words provide a useful source of information for Chinese NLP, and word segmentation has
been taken as a pre-processing step for most downstream tasks. For many NLP tasks …

Chinese chunking has traditionally been solved by assuming gold standard word
segmentation. We find that the accuracies drop drastically when automatic segmentation is …

Previous work has shown that joint modeling of two Natural Language Processing (NLP)
tasks are effective for achieving better performances for both tasks. Lots of task-specific joint …

We propose a neural probabilistic structured-prediction method for transition-based natural
language processing, which integrates beam search and contrastive learning. The method …

This chapter addresses Chinese noun phrase chunking with special reference to
nominalizations based on a semi-supervised approach. It uses YamCha, a support vector …

This paper aims at using clause boundary information to improve the performance of the
Chinese functional chunk parsing. Firstly, we propose a rule-based method using both …

Boundary recognition is an important research of natural language processing, and it
provides a basis for the application of Chinese word segmentation, chunk analysis, named …

标点符号的边界识别是自然语言处理的重要研究内容, 它是分词, 语块识别等应用的基础.
为了实现中文中用于表示并列成分分割的顿号的边界识别, 采用了用于序列分割和标记的条件随 …

Chunking is a crucial task in natural language processing. The task aims to divide a text into
syntactically correlated non-overlapping chunks. The discrete model and neural model can …