There are a large number of negative expressions in natural language texts.As a more fine-grained negative semantic analysis task,negative focus identification has begun to attract the attention of natural language processing(NLP)researchers in recent years.The task aims to identify the text fragments modified and emphasized by negative cues in the sentence,and it is of great significance to the downstream tasks of NLP,such as sentiment analysis and opinion mining.Compared with English,the study on negative focus identification for Chinese is currently slow,the main reason is that there is no Chinese dataset to provide training and test data for the models.To solve the above issue,this paper carried out the manual annotation of negative focuses on the Chinese Negative and Speculation corpus(CNeSp),initially explored the language phenomena of negative focus on Chinese,and constructed a dataset containing 5,762 samples.Besides,we also come up with a baseline system based on neural network model to provide a reference for subsequent studies.
否定焦点数据集人工标注
盛佳璇、邹博伟、沈龙骧、叶静、洪宇
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苏州大学计算机科学与技术学院,苏州,2150001
苏州大学计算机科学与技术学院,苏州,2150001,新加坡资讯通信研究院,新加坡,1386322
否定焦点 数据集 人工标注
Chinese National Conference on Computational Linguistic
Haikou(CN)
19th Chinese National Conference on Computational Linguistic
NETL
