Following the work of Stymne and Cancedda ( 2011 ) , we implement a linear-chain CRF merging system using the following features : stemmed ( separated ) surface form , part-of-speech14 and frequencies from the training corpus for bigrams/merging of word and word +1 , word as true prefix , word +1 as true suffix , plus frequency comparisons of these .
productive generation of compound words in statistical machine translation
Sara Stymne Nicola Cancedda
merge and ii ) how to merge . Following the work of Stymne and Cancedda ( 2011 ) , we implement a linear-chain CRF merging system using the following features : stemmed ( separated ) surface form , part-of-speech14 and frequencies from the training corpus for bigrams/merging of word and word +1 , word as true prefix , word +1 as true suffix , plus frequency comparisons of these . The CRF is trained on the split monolingual data .
Following the work of @@CITATION , we implement a linear-chain CRF merging system using the following features : stemmed ( separated ) surface form , part-of-speech14 and frequencies from the training corpus for bigrams/merging of word and word +1 , word as true prefix , word +1 as true suffix , plus frequency comparisons of these .