类 型
11 篇文献
 
Semi-supervised Discourse Relation Classification with Structural Learning  
Abstract. The corpora available for training discourse relation classifiers are annotated using a general set of discourse relations. However, for certain applications, custom discourse relations are ......
Conference on Intelligent Text Processing and Computational Linguistics  2011
0次引用 0 0
A Semi-Supervised Approach to Improve Classification of Infrequent Discourse Relations Using Feature Vector Extension  
u-tokyo.ac.jp Several recent discourse parsers have employed fully-supervised machine learning approaches. These methods require human annotators to beforehand create an extensive training corpus, whi......
Empirical Methods in Natural Language Processing  2010
3次引用 0 0
Predicting Discourse Connectives for Implicit Discourse Relation Recognition  
Existing works indicate that the absence of explicit discourse connectives makes it difficult to recognize implicit discourse relations. In this paper we attempt to overcome this difficulty for implic......
International Conference on Computational Linguistics  2010
3次引用 0 0
A PDTB-Styled End-to-End Discourse Parser  
We have developed a full discourse parser in the Penn Discourse Treebank (PDTB) style. Our trained parser first identifies all discourse and non-discourse relations, locates and labels their arguments......
Computing Research Repository  2010
1次引用 0 0
The Effects of Discourse Connectives Prediction on Implicit Discourse Relation Recognition  
Implicit discourse relation recognition is difficult due to the absence of explicit discourse connectives between arbitrary spans of text. In this paper, we use language models to predict the discours......
0次引用 0 0
Modelling Discourse Relations for Arabic  
We present the first algorithms to automatically identify explicit discourse connectives and the relations they signal for Arabic text. First we show that, for Arabic news, most adjacent sentences are......
0次引用 0 0
Improving Implicit Discourse Relation Recognition Through Feature Set Optimization  
We provide a systematic study of previously proposed features for implicit discourse relation identification, identifying new feature combinations that optimize F1-score. The resulting classifiers ach......
0次引用 0 0
Towards Semi-Supervised Classification of Discourse Relations using Feature Correlations  
Two of the main corpora available for training discourse relation classifiers are the RST Discourse Treebank (RST-DT) and the Penn Discourse Treebank (PDTB), which are both based on the Wall Street Jo......
0次引用 0 0
Using entity features to classify implicit discourse relations  
We report results on predicting the sense of implicit discourse relations between adjacent sentences in text. Our investigation concentrates on the association between discourse relations and properti......
2次引用 0 0
The Biomedical Discourse Relation Bank  
Background  Identification of discourse relations, such as causal and contrastive relations, between situations mentioned in text is an important task for biomedical text-mining. A biomedical text cor......
BMC Bioinformatics  2011
0次引用 0 0

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