{"title":"Chinese Grammatical Error Diagnosis System Based on Hybrid Model","authors":"Xiupeng Wu, Peijie Huang, Jundong Wang, Qingwen Guo, Yuhong Xu, Chuping Chen","doi":"10.18653/v1/W15-4418","DOIUrl":"https://doi.org/10.18653/v1/W15-4418","url":null,"abstract":"This paper describes our system in the Chinese Grammatical Error Diagnosis (CGED) task for learning Chinese as a Foreign Language (CFL). Our work adopts a hybrid model by integrating rulebased method and n-gram statistical method to detect Chinese grammatical errors, identify the error type and point out the position of error in the input sentences. Tri-gram is applied to disorder mistake. And the rest of mistakes are solved by the conservation rules sets. Empirical evaluation results demonstrate the utility of our CGED system.","PeriodicalId":316430,"journal":{"name":"NLP-TEA@ACL/IJCNLP","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123265771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Annotating Entailment Relations for Shortanswer Questions","authors":"Simon Ostermann, Andrea Horbach, Manfred Pinkal","doi":"10.18653/v1/W15-4408","DOIUrl":"https://doi.org/10.18653/v1/W15-4408","url":null,"abstract":"This paper presents an annotation project that explores the relationship between textual entailment and short answer scoring (SAS). We annotate entailment relations between learner and target answers in the Corpus of Reading Comprehension Exercises for German (CREG) with a finegrained label inventory and compare them in various ways to correctness scores assigned by teachers. Our main finding is that although both tasks are clearly related, not all of our entailment tags can be directly mapped to SAS scores and that especially the area of partial entailment covers instances that are problematic for automatic scoring and need further investigation.","PeriodicalId":316430,"journal":{"name":"NLP-TEA@ACL/IJCNLP","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125847387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Tao Chen, Naijia Zheng, Yue Zhao, Muthu Kumar Chandrasekaran, Min-Yen Kan
{"title":"Interactive Second Language Learning from News Websites","authors":"Tao Chen, Naijia Zheng, Yue Zhao, Muthu Kumar Chandrasekaran, Min-Yen Kan","doi":"10.18653/v1/W15-4406","DOIUrl":"https://doi.org/10.18653/v1/W15-4406","url":null,"abstract":"We propose WordNews, a web browser extension that allows readers to learn a second language vocabulary while reading news online. Injected tooltips allow readers to look up selected vocabulary and take simple interactive tests. We discover that two key system components needed improvement, both which stem from the need to model context. These two issues are real-world word sense disambiguation (WSD) to aid translation quality and constructing interactive tests. For the first, we start with Microsoft’s Bing translation API but employ additional dictionary-based heuristics that significantly improve translation in both coverage and accuracy. For the second, we propose techniques for generating appropriate distractors for multiple-choice word mastery tests. Our preliminary user survey confirms the need and viability of such a language learning platform.","PeriodicalId":316430,"journal":{"name":"NLP-TEA@ACL/IJCNLP","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134332441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Bilingual Keyword Extraction and its Educational Application","authors":"Chung-Chi Huang, Mei-hua Chen, Ping-Che Yang","doi":"10.18653/v1/W15-4407","DOIUrl":"https://doi.org/10.18653/v1/W15-4407","url":null,"abstract":"We introduce a method that extracts keywords in a language with the help of the other. The method involves estimating preferences for topical keywords and fusing language-specific word statistics. At run-time, we transform parallel articles into word graphs, build crosslingual edges for word statistics integration, and exploit PageRank with word keyness information for keyword extraction. We apply our method to keyword analysis and language learning. Evaluation shows that keyword extraction benefits from cross-language information and language learners benefit from our keywords in reading comprehension test.","PeriodicalId":316430,"journal":{"name":"NLP-TEA@ACL/IJCNLP","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115483129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"NTOU Chinese Grammar Checker for CGED Shared Task","authors":"Chuan-Jie Lin, Shao-Heng Chen","doi":"10.18653/v1/W15-4403","DOIUrl":"https://doi.org/10.18653/v1/W15-4403","url":null,"abstract":"Grammatical error diagnosis is an essential part in a language-learning tutoring system. Participating in the second Chinese grammar error detection task, we proposed a new system which measures the likelihood of sentences generated by deleting, inserting, or exchanging characters or words. Two sentence likelihood functions were proposed based on frequencies of spaceremoved version of Google n-grams. The best system achieved a precision of 23.4% and a recall of 36.4% in the identification level.","PeriodicalId":316430,"journal":{"name":"NLP-TEA@ACL/IJCNLP","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122299919","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Grammatical Error Correction Considering Multi-word Expressions","authors":"Tomoya Mizumoto, Masato Mita, Yuji Matsumoto","doi":"10.18653/v1/W15-4412","DOIUrl":"https://doi.org/10.18653/v1/W15-4412","url":null,"abstract":"Multi-word expressions (MWEs) have been recognized as important linguistic information and much research has been conducted especially on their extraction and interpretation. On the other hand, they have hardly been used in real application areas. While those who are learning English as a second language (ESL) use MWEs in their writings just like native speakers, MWEs haven’t been taken into consideration in grammatical error correction tasks. In this paper, we investigate the grammatical error correction method using MWEs. Our method proposes a straightforward application of MWEs to grammatical error correction, but experimental results show that MWEs have a beneficial effect on grammatical error correction.","PeriodicalId":316430,"journal":{"name":"NLP-TEA@ACL/IJCNLP","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125220922","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Condition Random Fields-based Grammatical Error Detection for Chinese as Second Language","authors":"Jui-Feng Yeh, Chan-Kun Yeh, Kai-Hsiang Yu, Ya-Ting Li, Wanyu Tsai","doi":"10.18653/v1/W15-4416","DOIUrl":"https://doi.org/10.18653/v1/W15-4416","url":null,"abstract":"The foreign learners are not easy to learn Chinese as a second language. Because there are many special rules different from other languages in Chinese. When the people learn Chinese as a foreign language usually make some grammatical errors, such as missing, redundant, selection and disorder. In this paper, we proposed the conditional random fields (CRFs) to detect the grammatical errors. The features based on statistical word and part-ofspeech (POS) pattern were adopted here. The relationships between words by part-of-speech are helpful for Chinese grammatical error detection. Finally, we according to CRF determined which error types in sentences. According to the observation of experimental results, the performance of the proposed model is acceptable in precision and recall rates.","PeriodicalId":316430,"journal":{"name":"NLP-TEA@ACL/IJCNLP","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126553430","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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