Chinese Named Entity Recognition

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

7 leaderboard tables shown for this task, 7 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

6 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 40 papers with code (75 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• ERNIE: Enhanced Representation through Knowledge Integration
  19 Apr 2019 19 repositories listed Syntology ran 0 of 7 samples · 7 unverified
  We present a novel language representation model enhanced by knowledge called ERNIE (Enhanced Representation through kNowledge IntEgration).
• A Unified MRC Framework for Named Entity Recognition
  25 Oct 2019 8 repositories listed Syntology ran 2 of 5 samples · 3 unverified · 2 pointer-only (licence)
  Instead of treating the task of NER as a sequence labeling problem, we propose to formulate it as a machine reading comprehension (MRC) task.
• ZEN: Pre-training Chinese Text Encoder Enhanced by N-gram Representations
  2 Nov 2019 7 repositories listed Syntology ran 7 of 35 samples · 28 unverified
  Moreover, it is shown that reasonable performance can be obtained when ZEN is trained on a small corpus, which is important for applying pre-training techniques to scenarios with limited data.
• TENER: Adapting Transformer Encoder for Named Entity Recognition
  10 Nov 2019 6 repositories listed Syntology ran 0 of 1 samples · 1 unverified
  The Bidirectional long short-term memory networks (BiLSTM) have been widely used as an encoder in models solving the named entity recognition (NER) task.
• Dice Loss for Data-imbalanced NLP Tasks
  7 Nov 2019 4 repositories listed Syntology ran 0 of 3 samples · 3 unverified
  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…
• DiffusionNER: Boundary Diffusion for Named Entity Recognition
  22 May 2023 3 repositories listed
  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.
• Improving Named Entity Recognition by External Context Retrieving and Cooperative Learning
  8 May 2021 3 repositories listed Syntology ran 0 of 4 samples · 4 unverified
  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…
• CLUENER2020: Fine-grained Named Entity Recognition Dataset and Benchmark for Chinese
  13 Jan 2020 3 repositories listed
  In this paper, we introduce the NER dataset from CLUE organization (CLUENER2020), a well-defined fine-grained dataset for named entity recognition in Chinese.
• ERNIE 2.0: A Continual Pre-training Framework for Language Understanding
  29 Jul 2019 3 repositories listed Syntology ran 0 of 1 samples · 1 unverified · 1 pointer-only (licence)
  Recently, pre-trained models have achieved state-of-the-art results in various language understanding tasks, which indicates that pre-training on large-scale corpora may play a crucial role in natural language…
• Chinese NER Using Lattice LSTM
  5 May 2018 3 repositories listed Syntology ran 2 of 2 samples · 0 unverified · 2 pointer-only (licence)
  We investigate a lattice-structured LSTM model for Chinese NER, which encodes a sequence of input characters as well as all potential words that match a lexicon.
• Unsupervised Boundary-Aware Language Model Pretraining for Chinese Sequence Labeling
  27 Oct 2022 2 repositories listed
  We apply BABERT for feature induction of Chinese sequence labeling tasks.
• Simplify the Usage of Lexicon in Chinese NER
  16 Aug 2019 2 repositories listed
  This method avoids designing a complicated sequence modeling architecture, and for any neural NER model, it requires only subtle adjustment of the character representation layer to introduce the lexicon information.
• Glyce: Glyph-vectors for Chinese Character Representations
  29 Jan 2019 2 repositories listed Syntology ran 3 of 8 samples · 5 unverified
  However, due to the lack of rich pictographic evidence in glyphs and the weak generalization ability of standard computer vision models on character data, an effective way to utilize the glyph information remains to be…
• Student-Powered Digital Scholarship CoLab Project in the HKUST Library: Develop a Chinese Named-Entity Recognition (NER) Tool within One Semester from the Ground Up
  29 Mar 2025 1 repository listed
  The Library offers 1-2 projects per year for students to engage with advanced technologies in practical contexts while supporting the Library in tackling challenges and streamlining operational tasks.
• HREB-CRF: Hierarchical Reduced-bias EMA for Chinese Named Entity Recognition
  3 Mar 2025 1 repository listed
  Incorrect boundary division, complex semantic representation, and differences in pronunciation and meaning often lead to errors in Chinese Named Entity Recognition(CNER).
• Supplementary Features of BiLSTM for Enhanced Sequence Labeling
  31 May 2023 1 repository listed
  Sequence labeling tasks require the computation of sentence representations for each word within a given sentence.
• Rethinking the Value of Gazetteer in Chinese Named Entity Recognition
  6 Jul 2022 1 repository listed
  Gazetteer is widely used in Chinese named entity recognition (NER) to enhance span boundary detection and type classification.
• NFLAT: Non-Flat-Lattice Transformer for Chinese Named Entity Recognition
  12 May 2022 1 repository listed
  To deal with this issue, we advocate a novel lexical enhancement method, InterFormer, that effectively reduces the amount of computational and memory costs by constructing non-flat lattices.
• Boundary Smoothing for Named Entity Recognition
  26 Apr 2022 1 repository listed
  Neural named entity recognition (NER) models may easily encounter the over-confidence issue, which degrades the performance and calibration.
• Parallel Instance Query Network for Named Entity Recognition
  20 Mar 2022 1 repository listed
  Each instance query predicts one entity, and by feeding all instance queries simultaneously, we can query all entities in parallel.
• MarkBERT: Marking Word Boundaries Improves Chinese BERT
  12 Mar 2022 1 repository listed
  We present a Chinese BERT model dubbed MarkBERT that uses word information in this work.
• Unified Named Entity Recognition as Word-Word Relation Classification
  19 Dec 2021 1 repository listed
  So far, named entity recognition (NER) has been involved with three major types, including flat, overlapped (aka.
• MarkBERT: Marking Word Boundaries Improves Chinese BERT
  16 Nov 2021 1 repository listed
  We present a Chinese BERT model dubbed MarkBERT that uses word information in this work.
• MFE-NER: Multi-feature Fusion Embedding for Chinese Named Entity Recognition
  16 Sep 2021 1 repository listed
  Some Chinese characters are quite similar as they share the same components or have similar pronunciations.
• Enhancing Entity Boundary Detection for Better Chinese Named Entity Recognition
  1 Aug 2021 1 repository listed
  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
  12 Jul 2021 1 repository listed
  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
  14 May 2021 1 repository listed
  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…
• Improving Named Entity Recognition with Attentive Ensemble of Syntactic Information
  29 Oct 2020 1 repository listed
  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
  29 Oct 2020 1 repository listed
  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.
• SLK-NER: Exploiting Second-order Lexicon Knowledge for Chinese NER
  16 Jul 2020 1 repository listed
  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.

Syntology lines on 9 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.