Gaoqi Rao

Also published as: Gaoqi RAO


2022

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Proceedings of the 21st Chinese National Conference on Computational Linguistics
Maosong Sun (孙茂松) | Yang Liu (刘洋) | Wanxiang Che (车万翔) | Yang Feng (冯洋) | Xipeng Qiu (邱锡鹏) | Gaoqi Rao (饶高琦) | Yubo Chen (陈玉博)
Proceedings of the 21st Chinese National Conference on Computational Linguistics

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基于《同义词词林》的中文语体分类资源构建(Construction of Chinese register classification resources based on “Tongyici Cilin”)
Guojing Huang (黄国敬) | Liwei Zhou (周立炜) | Gaoqi Rao (饶高琦) | Jiaojiao Zang (臧娇娇)
Proceedings of the 21st Chinese National Conference on Computational Linguistics

“语体词是指在某一语体中专用的词语,是语体的语言要素和形式标记。而语体词的资源可以服务于与现实场景息息相关的NLP应用,但目前此类资源较为稀缺。对此,本文基于《大词林》,完成了“语体词标注”“语体(词)链条标注”和“平行构式标注”三个任务,建立了以语体词为基础的语体分类资源。本资源包含55,710条词语、5017个语体链条和433组平行构式。基于此本文分析中文语体词的分布概况、形态差异以及词义词性的分布情况。”

2021

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Proceedings of the 20th Chinese National Conference on Computational Linguistics
Sheng Li (李生) | Maosong Sun (孙茂松) | Yang Liu (刘洋) | Hua Wu (吴华) | Kang Liu (刘康) | Wanxiang Che (车万翔) | Shizhu He (何世柱) | Gaoqi Rao (饶高琦)
Proceedings of the 20th Chinese National Conference on Computational Linguistics

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基于结构树库的状位动词语义分类及搭配库构建(Semantic Classification of Adverbial Verbs Based on Structure Tree Database and Construction of Collocation Database)
Tian Shao (邵田) | Shiquan Zhai (翟世权) | Gaoqi Rao (饶高琦) | Endong Xun (荀恩东)
Proceedings of the 20th Chinese National Conference on Computational Linguistics

一般情况下,一个小句中只有一个动词,但是也有两个动词同时在一个小句中出现的情况,比如两个动词接连出现在同一小句中,在句法上有可能构成状中、述补、动宾、连谓及并列等结构,语义上可能表示修饰、支配、并列等关系。连续使用的两个动词构成了相对复杂的结构与语义关系,尤其是在没有形式标记的情况下,如何自动识别连用动词的结构及其所表达的语义关系是句法语义分析在落地过程中面对的较为困难的问题。对此,本文将研究对象定位于直接作状语的动词,从大规模结构树库中抽取两个动词连用的情况,并对语料进行消歧,提取出作状语的动词后,进一步对其进行语义的细分类,最后构建相应的语义搭配库。不仅为语言学本体提供了分类参考,同时也为深层次的汉语句法语义分析提供了更多的知识。

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汉语语体特征的计量与分类研究(A study on the measurement and classification of Chinese stylistic features)
Qinqing Tai (邰沁清) | Gaoqi Rao (饶高琦)
Proceedings of the 20th Chinese National Conference on Computational Linguistics

本文运用语料库和统计方法对汉语语体进行特征的计量研究,并进一步实现自动分类任务。首先通过单因素方差分析描述语体特征区别不同语体的作用和功能。其次,选取其中具有区分度的语言要素拟合逻辑回归模型,量化语体表达形式并观察特征对语体构成的重要性,并通过聚类计算得到了语体的范畴分类体系。最后,以具有代表性的机器学习模型为分类器,挖掘不同组合特征的结构对于语体自动分类的影响。得出在“词2n+词类2n+标点符号2n+语言特征”的组合特征上,取得了最好的分类结果,随机森林模型达到97.25%的准确率。

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基于结构检索的汉语介动搭配知识库构建(Construction of Preposition-verb Knowledge Base Based on Structure Retrieval)
Chengwen Wang (王诚文) | Gaoqi Rao (饶高琦) | Endong Xun (荀恩东)
Proceedings of the 20th Chinese National Conference on Computational Linguistics

以往的介词知识库构建重视介词语义和介宾的搭配研究,鲜有对介动搭配进行系统研究及知识获取的工作。而汉语介词发达及动词是句子中心的特征决定了介动搭配研究的重要性。本研究基于结构检索技术,充分借助短语结构属性和结构信息,从大规模语料中抽取介动搭配16033对。并提出了介动搭配紧密度的度量方法,初步分析证明其远优于依靠绝对频次进行搭配度量的方法。

2020

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Proceedings of the 6th Workshop on Natural Language Processing Techniques for Educational Applications
Erhong YANG | Endong XUN | Baolin ZHANG | Gaoqi RAO
Proceedings of the 6th Workshop on Natural Language Processing Techniques for Educational Applications

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Overview of NLPTEA-2020 Shared Task for Chinese Grammatical Error Diagnosis
Gaoqi Rao | Erhong Yang | Baolin Zhang
Proceedings of the 6th Workshop on Natural Language Processing Techniques for Educational Applications

This paper presents the NLPTEA 2020 shared task for Chinese Grammatical Error Diagnosis (CGED) which seeks to identify grammatical error types, their range of occurrence and recommended corrections within sentences written by learners of Chinese as a foreign language. We describe the task definition, data preparation, performance metrics, and evaluation results. Of the 30 teams registered for this shared task, 17 teams developed the system and submitted a total of 43 runs. System performances achieved a significant progress, reaching F1 of 91% in detection level, 40% in position level and 28% in correction level. All data sets with gold standards and scoring scripts are made publicly available to researchers.

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A Corpus Linguistic Perspective on the Appropriateness of Pop Songs for Teaching Chinese as a Second Language
Xiangyu Chi | Gaoqi Rao
Proceedings of the 6th Workshop on Natural Language Processing Techniques for Educational Applications

Language and music are closely related. Regarding the linguistic feature richness, pop songs are probably suitable to be used as extracurricular materials in language teaching. In order to prove this point, this paper presents the Contemporary Chinese Pop Lyrics (CCPL) corpus. Based on that, we investigated and evaluated the appropriateness of pop songs for Teaching Chinese as a Second Language (TCSL) with the assistance of Natural Language Processing methods from the perspective of Chinese character coverage, lexical coverage and the addressed topic similarity. Some suggestions in Chinese teaching with the aid of pop lyrics are provided.

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中文问句的形式分类和资源建设(Formal classification and resource construction of Chinese questions)
Jiangtao Li (黎江涛) | Gaoqi Rao (饶高琦)
Proceedings of the 19th Chinese National Conference on Computational Linguistics

本文归纳了问句形式在问句语料筛选中的作用,探索了问句分类必需的形式特征,同时通过人工标注建设了中文问句分类语料库,并在此基础上进行了基于规则和统计的分类实验,通过多轮实验迭代优化特征组合形成特征规则集,为当前问答提供形式上的分类基础。实验中,基于优化特征规则集的有限状态自动机可实现宏平均F1值为0.94;统计机器学习中随机森林模型的分类效果较好,F1值宏平均达到0.98,表明问句形式分类具有相当可行性和准确性。

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基于组块分析的汉语块依存语法(Chinese Chunk-Based Dependency Grammar)
Qingqing Qian (钱青青) | Chengwen Wang (王诚文) | Gaoqi Rao (饶高琦) | Endong Xun (荀恩东)
Proceedings of the 19th Chinese National Conference on Computational Linguistics

基于词单元的经典依存语法在面向中文的句子分析中遇到诸多汉语特性引起的困难。为此,本文提出汉语的块依存语法,以谓词为核心,以组块为研究对象,在句内和句间寻找谓词所支配的组块,构建句群级别的句法分析框架。这一操作不仅仅是提升叶子节点的语言单位,而且还针对汉语语义特点进行了分析方式和分析规则上的创新,能够较好地解决微观层次的逻辑结构知识,并为中观论元知识和宏观篇章知识打好铺垫。本文主要介绍了块依存语法理念、表示、分析方法及特点,并简要介绍了块依存树库的构建情况。截至目前为止,树库规模为187万字符(超过4万复句、10万小句),其中包含67%新闻文本和32%百科文本。

2018

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Overview of NLPTEA-2018 Share Task Chinese Grammatical Error Diagnosis
Gaoqi Rao | Qi Gong | Baolin Zhang | Endong Xun
Proceedings of the 5th Workshop on Natural Language Processing Techniques for Educational Applications

This paper presents the NLPTEA 2018 shared task for Chinese Grammatical Error Diagnosis (CGED) which seeks to identify grammatical error types, their range of occurrence and recommended corrections within sentences written by learners of Chinese as foreign language. We describe the task definition, data preparation, performance metrics, and evaluation results. Of the 20 teams registered for this shared task, 13 teams developed the system and submitted a total of 32 runs. Progress in system performances was obviously, reaching F1 of 36.12% in position level and 25.27% in correction level. All data sets with gold standards and scoring scripts are made publicly available to researchers.

2017

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IJCNLP-2017 Task 1: Chinese Grammatical Error Diagnosis
Gaoqi Rao | Baolin Zhang | Endong Xun | Lung-Hao Lee
Proceedings of the IJCNLP 2017, Shared Tasks

This paper presents the IJCNLP 2017 shared task for Chinese grammatical error diagnosis (CGED) which seeks to identify grammatical error types and their range of occurrence within sentences written by learners of Chinese as foreign language. We describe the task definition, data preparation, performance metrics, and evaluation results. Of the 13 teams registered for this shared task, 5 teams developed the system and submitted a total of 13 runs. We expected this evaluation campaign could lead to the development of more advanced NLP techniques for educational applications, especially for Chinese error detection. All data sets with gold standards and scoring scripts are made publicly available to researchers.

2016

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Overview of NLP-TEA 2016 Shared Task for Chinese Grammatical Error Diagnosis
Lung-Hao Lee | Gaoqi Rao | Liang-Chih Yu | Endong Xun | Baolin Zhang | Li-Ping Chang
Proceedings of the 3rd Workshop on Natural Language Processing Techniques for Educational Applications (NLPTEA2016)

This paper presents the NLP-TEA 2016 shared task for Chinese grammatical error diagnosis which seeks to identify grammatical error types and their range of occurrence within sentences written by learners of Chinese as foreign language. We describe the task definition, data preparation, performance metrics, and evaluation results. Of the 15 teams registered for this shared task, 9 teams developed the system and submitted a total of 36 runs. We expected this evaluation campaign could lead to the development of more advanced NLP techniques for educational applications, especially for Chinese error detection. All data sets with gold standards and scoring scripts are made publicly available to researchers.