Paper Reading AI Learner

N-LTP: A Open-source Neural Chinese Language Technology Platform with Pretrained Models

2020-09-24 11:45:39
Wanxiang Che, Yunlong Feng, Libo Qin, Ting Liu

Abstract

We introduce \texttt{N-LTP}, an open-source Python Chinese natural language processing toolkit supporting five basic tasks: Chinese word segmentation, part-of-speech tagging, named entity recognition, dependency parsing, and semantic dependency parsing. \texttt{N-LTP} adopts the multi-task framework with the pre-trained model to capture the shared knowledge across all Chinese relevant tasks. In addition, we propose to use knowledge distillation where single-task models teach a multi-task model, helping the multi-task model surpass its single-task teachers. Finally, we provide fundamental tasks API and a visualization tool to make users easier to use and view the processing results directly. To the best of our knowledge, this is the first toolkit to support all Chinese NLP fundamental tasks. Source code, documentation, and pre-trained models are available at this https URL.

Abstract (translated)

URL

https://arxiv.org/abs/2009.11616

PDF

https://arxiv.org/pdf/2009.11616.pdf


Tags
3D Action Action_Localization Action_Recognition Activity Adversarial Agent Attention Autonomous Bert Boundary_Detection Caption Chat Classification CNN Compressive_Sensing Contour Contrastive_Learning Deep_Learning Denoising Detection Dialog Diffusion Drone Dynamic_Memory_Network Edge_Detection Embedding Embodied Emotion Enhancement Face Face_Detection Face_Recognition Facial_Landmark Few-Shot Gait_Recognition GAN Gaze_Estimation Gesture Gradient_Descent Handwriting Human_Parsing Image_Caption Image_Classification Image_Compression Image_Enhancement Image_Generation Image_Matting Image_Retrieval Inference Inpainting Intelligent_Chip Knowledge Knowledge_Graph Language_Model Matching Medical Memory_Networks Multi_Modal Multi_Task NAS NMT Object_Detection Object_Tracking OCR Ontology Optical_Character Optical_Flow Optimization Person_Re-identification Point_Cloud Portrait_Generation Pose Pose_Estimation Prediction QA Quantitative Quantitative_Finance Quantization Re-identification Recognition Recommendation Reconstruction Regularization Reinforcement_Learning Relation Relation_Extraction Represenation Represenation_Learning Restoration Review RNN Salient Scene_Classification Scene_Generation Scene_Parsing Scene_Text Segmentation Self-Supervised Semantic_Instance_Segmentation Semantic_Segmentation Semi_Global Semi_Supervised Sence_graph Sentiment Sentiment_Classification Sketch SLAM Sparse Speech Speech_Recognition Style_Transfer Summarization Super_Resolution Surveillance Survey Text_Classification Text_Generation Tracking Transfer_Learning Transformer Unsupervised Video_Caption Video_Classification Video_Indexing Video_Prediction Video_Retrieval Visual_Relation VQA Weakly_Supervised Zero-Shot