Chinese Named Entity Recognition

37 papers with code • 7 benchmarks • 6 datasets

Chinese named entity recognition is a subtask of information extraction that seeks to locate and classify named entities mentioned in unstructured text into pre-defined categories such as person names, organizations, locations, medical codes, time expressions, quantities, monetary values, percentages, etc. from Chinese text (Source: Adapted from Wikipedia).

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2 papers
6,162

Most implemented papers

Dice Loss for Data-imbalanced NLP Tasks

ShannonAI/dice_loss_for_NLP ACL 2020

Many NLP tasks such as tagging and machine reading comprehension are faced with the severe data imbalance issue: negative examples significantly outnumber positive examples, and the huge number of background examples (or easy-negative examples) overwhelms the training.

Unsupervised Boundary-Aware Language Model Pretraining for Chinese Sequence Labeling

modelscope/AdaSeq 27 Oct 2022

We apply BABERT for feature induction of Chinese sequence labeling tasks.

DiffusionNER: Boundary Diffusion for Named Entity Recognition

tricktreat/diffusionner 22 May 2023

In this paper, we propose DiffusionNER, which formulates the named entity recognition task as a boundary-denoising diffusion process and thus generates named entities from noisy spans.

Distantly Supervised NER with Partial Annotation Learning and Reinforcement Learning

rainarch/DSNER COLING 2018

A bottleneck problem with Chinese named entity recognition (NER) in new domains is the lack of annotated data.

Adversarial Transfer Learning for Chinese Named Entity Recognition with Self-Attention Mechanism

CPF-NLPR/AT4ChineseNER EMNLP 2018

However, existing methods for Chinese NER either do not exploit word boundary information from CWS or cannot filter the specific information of CWS.

CAN-NER: Convolutional Attention Network for Chinese Named Entity Recognition

microsoft/vert-papers NAACL 2019

Named entity recognition (NER) in Chinese is essential but difficult because of the lack of natural delimiters.

Neural Chinese Named Entity Recognition via CNN-LSTM-CRF and Joint Training with Word Segmentation

rxy007/cnn-lstm-crf 26 Apr 2019

Besides, the training data for CNER in many domains is usually insufficient, and annotating enough training data for CNER is very expensive and time-consuming.

Exploiting Multiple Embeddings for Chinese Named Entity Recognition

WHUIR/ME-CNER 28 Aug 2019

Identifying the named entities mentioned in text would enrich many semantic applications at the downstream level.

Dependency-Guided LSTM-CRF for Named Entity Recognition

allanj/ner_with_dependency IJCNLP 2019

Dependency tree structures capture long-distance and syntactic relationships between words in a sentence.

Leverage Lexical Knowledge for Chinese Named Entity Recognition via Collaborative Graph Network

DianboWork/Graph4CNER IJCNLP 2019

The lack of word boundaries information has been seen as one of the main obstacles to develop a high performance Chinese named entity recognition (NER) system.