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).
Benchmarks
These leaderboards are used to track progress in Chinese Named Entity Recognition
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Libraries
Use these libraries to find Chinese Named Entity Recognition models and implementations
OntoNotes 5.0
Weibo NER
Resume NER
Latest papers
Enhancing Entity Boundary Detection for Better Chinese Named Entity Recognition
cchen-reese/Boundary-Enhanced-NER
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ACL 2021
In comparison with English, due to the lack of explicit word boundary and tenses information, Chinese Named Entity Recognition (NER) is much more challenging.
MECT: Multi-Metadata Embedding based Cross-Transformer for Chinese Named Entity Recognition
CoderMusou/MECT4CNER
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ACL 2021
This paper presents a novel Multi-metadata Embedding based Cross-Transformer (MECT) to improve the performance of Chinese NER by fusing the structural information of Chinese characters.
Locate and Label: A Two-stage Identifier for Nested Named Entity Recognition
tricktreat/locate-and-label
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ACL 2021
Although these methods have the innate ability to handle nested NER, they suffer from high computational cost, ignorance of boundary information, under-utilization of the spans that partially match with entities, and difficulties in long entity recognition.
Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning
modelscope/AdaSeq
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ACL 2021
We find empirically that the contextual representations computed on the retrieval-based input view, constructed through the concatenation of a sentence and its external contexts, can achieve significantly improved performance compared to the original input view based only on the sentence.
Named Entity Recognition for Social Media Texts with Semantic Augmentation
cuhksz-nlp/SANER
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EMNLP 2020
In particular, we obtain the augmented semantic information from a large-scale corpus, and propose an attentive semantic augmentation module and a gate module to encode and aggregate such information, respectively.
Improving Named Entity Recognition with Attentive Ensemble of Syntactic Information
cuhksz-nlp/AESINER
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Findings of the Association for Computational Linguistics 2020
Named entity recognition (NER) is highly sensitive to sentential syntactic and semantic properties where entities may be extracted according to how they are used and placed in the running text.
SLK-NER: Exploiting Second-order Lexicon Knowledge for Chinese NER
Although character-based models using lexicon have achieved promising results for Chinese named entity recognition (NER) task, some lexical words would introduce erroneous information due to wrongly matched words.
FLAT: Chinese NER Using Flat-Lattice Transformer
LeeSureman/Flat-Lattice-Transformer
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ACL 2020
Recently, the character-word lattice structure has been proved to be effective for Chinese named entity recognition (NER) by incorporating the word information.
FGN: Fusion Glyph Network for Chinese Named Entity Recognition
Except for adding glyph information, this method may also add extra interactive information with the fusion mechanism.
CLUENER2020: Fine-grained Named Entity Recognition Dataset and Benchmark for Chinese
In this paper, we introduce the NER dataset from CLUE organization (CLUENER2020), a well-defined fine-grained dataset for named entity recognition in Chinese.
