Results 11 to 20 of about 1,332,615 (213)
A Mixed Semantic Features Model for Chinese NER with Characters and Words [PDF]
Advances in Information Retrieval, 2020 Named Entity Recognition (NER) is an essential part of many natural language processing (NLP) tasks. The existing Chinese NER methods are mostly based on word segmentation, or use the character sequences as input. However, using a single granularity representation would suffer from the problems of out-of-vocabulary and word segmentation errors, and the
Chang N, Zhong J, Li Q, Zhu J.
europepmc +4 more sources
CRENER: A Character Relation Enhanced Chinese NER Model
CoRRChinese Named Entity Recognition (NER) is an important task in information extraction, which has a significant impact on downstream applications. Due to the lack of natural separators in Chinese, previous NER methods mostly relied on external dictionaries to enrich the semantic and boundary information of Chinese words.
Yaqiong Qiao, Shixuan Peng
openaire +4 more sources
A Local Information Perception Enhancement–Based Method for Chinese NER
Applied Sciences, 2023 Integrating lexical information into Chinese character embedding is a valid method to figure out the Chinese named entity recognition (NER) issue. However, most existing methods focus only on the discovery of named entity boundaries, considering only the
Miao Zhang, Ling Lu
doaj +2 more sources
Adversarial Learning for Chinese NER From Crowd Annotations
Proceedings of the AAAI Conference on Artificial Intelligence, 2018 To quickly obtain new labeled data, we can choose crowdsourcing as an alternative way at lower cost in a short time. But as an exchange, crowd annotations from non-experts may be of lower quality than those from experts. In this paper, we propose an approach to performing crowd annotation learning for Chinese Named Entity Recognition ...
YaoSheng Yang +5 more
openaire +3 more sources
CMNER: A Chinese Multimodal NER Dataset based on Social Media [PDF]
CoRRMultimodal Named Entity Recognition (MNER) is a pivotal task designed to extract named entities from text with the support of pertinent images. Nonetheless, a notable paucity of data for Chinese MNER has considerably impeded the progress of this natural language processing task within the Chinese domain.
Yuanze Ji +5 more
core +5 more sources
MP-NER: Morpho-Phonological Integration Embedding for Chinese Named Entity Recognition
IEEE AccessNamed Entity Recognition (NER) aims to automatically extract specific entities from unstructured text. Compared with English NER, Chinese NER faces challenges due to heterophony, where the same Chinese character may have different pronunciations and ...
Pu Li +5 more
doaj +2 more sources
Chinese NER based on improved Transformer encoder
网络与信息安全学报, 2021 In order to improve the effect of chinese named entity recognition, a method based on the XLNET- Transformer_P-CRF model was proposed, which used the Transformer_P encoder, improved the shortcomings of the traditional Transformer encoder that couldn’t ...
ZHENG Honghao, YU Hongtao, LI Shaomei
doaj +5 more sources
Simplify the Usage of Lexicon in Chinese NER [PDF]
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020 Recently, many works have tried to augment the performance of Chinese named entity recognition (NER) using word lexicons. As a representative, Lattice-LSTM has achieved new benchmark results on several public Chinese NER datasets. However, Lattice-LSTM has a complex model architecture.
Ruotian Ma +4 more
openaire +2 more sources
Porous Lattice Transformer Encoder for Chinese NER [PDF]
Proceedings of the 28th International Conference on Computational Linguistics, 2020 Incorporating lexicons into character-level Chinese NER by lattices is proven effective to exploitrich word boundary information. Previous work has extended RNNs to consume lattice inputsand achieved great success. However, due to the DAG structure and the inherently unidirectionalsequential nature, this method precludes batched computation and ...
Mengge Xue +5 more
openaire +1 more source
Chinese NER Using Lattice LSTM [PDF]
Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2018 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. Compared with character-based methods, our model explicitly leverages word and word sequence information.
Yue Zhang 0004, Jie Yang 0039
openaire +4 more sources