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
Most implemented papers
Chinese Named Entity Recognition Augmented with Lexicon Memory
dugu9sword/LEMON
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Inspired by a concept of content-addressable retrieval from cognitive science, we propose a novel fragment-based model augmented with a lexicon-based memory for Chinese NER, in which both the character-level and word-level features are combined to generate better feature representations for possible name candidates.
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.
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.
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.
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.
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.
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.
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.
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.
MarkBERT: Marking Word Boundaries Improves Chinese BERT
daiyongya/markbert
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ACL ARR November 2021
We present a Chinese BERT model dubbed MarkBERT that uses word information in this work.
