{"id":151580,"date":"2019-01-17T09:59:09","date_gmt":"2019-01-17T17:59:09","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/extraposition-a-case-study-in-german-sentence-realization\/"},"modified":"2019-01-17T09:59:09","modified_gmt":"2019-01-17T17:59:09","slug":"extraposition-a-case-study-in-german-sentence-realization","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/extraposition-a-case-study-in-german-sentence-realization\/","title":{"rendered":"Extraposition: A Case Study In German Sentence Realization"},"content":{"rendered":"
We profile the occurrence of clausal extraposition in corpora from different domains and demonstrate that extraposition is a pervasive phenomenon in German that must be addressed in German sentence realization. We present two different approaches to the modeling of extraposition, both based on machine learned decision tree classifiers. The two approaches differ in their view of the movement operation: one approach models multi-step movement through intermediate nodes to the ultimate target node, while the other approach models one-step movement to the target node. We compare the resulting models, trained on data from two domains and discuss the differences between the two types of models and between the results obtained in the different domains.<\/p>\n<\/div>\n
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We profile the occurrence of clausal extraposition in corpora from different domains and demonstrate that extraposition is a pervasive phenomenon in German that must be addressed in German sentence realization. We present two different approaches to the modeling of extraposition, both based on machine learned decision tree classifiers. 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