这种命名的规律性可以很好的帮助识别实体的组成和类型,论文中将这种规律性称为某一类型的实体所包含的特定内部模式。 we refer to regularity as specific internal patterns contained in a type of entity 进一步思考,这种命名的规律虽然能带来许多帮助,但同时也会产生一定的干扰,错误划分实体边界。如上图中(b),XX-...
原文链接:Named Entity Recognition for Chinese Social Media with Jointly Trained Embeddings 来源:EMNLP 问题介绍:命名实体识别(Named Entity Recognition) 命名实体识别是指从文本中识别出特定类型的实体,例如人名、地名等。它是自然语言处理的一个基础任务,它可以被用于关系抽取、实体链接等其他任务当中。命名实体识别...
Named Entity Recognition (NER) is an important basic task in natural language processing (NLP). In recent years, the method of word representations enhancement by character embedding has significantly enhanced the effect of entity recognition. However, this kind of character embedding method only ...
Inspired by the concept of content-addressable retrieval from cognitive science, we propose a novel fragment-based Chinese named entity recognition (NER) model augmented with a lexicon-based memory in which both character-level and word-level features ar
【论文阅读】MECT: Multi-Metadata Embedding based Cross-Transformer for Chinese Named Entity Recognition 论文地址:https://aclanthology.org/2021.acl-long.121.pdf 代码地址:https://github.com/CoderMusou/MECT4CNER Abstract 近年来,在中文命名实体识别(NER)中,词语增强已成为一种非常流行的方法,它可以减少...
Exploiting Multiple Embeddings for Chinese Named Entity Recognition 利用多个嵌入进行中文命名实体识别 代码:ME-CNER https://arxiv.org/pdf/1908.10657.pdf 识别文本中提到的命名实体将在下游级别丰富许多语义应用程序。 但是,由于在微博中普遍使用口语,因此与在正式中文语料库中执行NER相比,中文微博中的命名实体识别(...
Named entity recognition (NER) in Chinese is essential but difficult because of the lack of natural delimiters. Therefore, Chinese Word Segmentation (CWS) is usually considered as the first step for Chinese NER. However, models based on word-level embeddings and lexicon features ...
The Chinese named entity recognition (NER) task is a sub-task within the information extraction domain, where the task goal is to find, identify and classify relevant entities, such as names of people, places and organizations, from sentences given a pie
NER 模型(Chinese NER Using Lattice LSTM、Neural Adaptation Layers for Cross-domain Named Entity Recognition) 1. Information 命名实体识别(Named entity recognition)作为NLP的最基本任务,其早在上世纪80年代就已被广泛研究,今年来随着以神经网络为主导的Deep learning复苏,NER任务精度被不断提高。NER问题即为从句...
A Unified MRC Framework for Named Entity Recognition 本文彻底放弃了序列标注模型,用阅读理解的方法处理嵌套实体,即预测起止位置和实体分类;由起止位置标识的实体当然允许覆盖,自然就解决了嵌套问题;熟悉MRC的同学很快就会发现,通常的MRC只有一个答案span,然而一句话中可能存在多个实体span,怎么表示多个实体?因此本文修...