D10-1029 could transfer to conventional morphological segmentations . We extract all verbs in CELEX
C94-1036 only language which needs the morphological segmentation . For example , Chinese and Korean
C92-4195 shows the architecture of the morphological segmentation system . The interpreter for
C04-1152 prime candidate for recursive morphological segmentation . Results for Models 1 and 2
D10-1079 disambiguation ( tagging ) , given morphological segmentation in the output of the morphological
C92-4195 in Wothke/Schmidt ( 1991 ) . A morphological segmentation procedure for German has to deal
D10-1029 trained and tested on conventional morphological segmentations . 5.1 Analysis of Annotations
D10-1029 test our system on conventional morphological segmentations . Our classifier remains reliable
D10-1029 trained and tested on conventional morphological segmentations of prefix verbs . 1 Introduction
C04-1152 efficient algorithm for greedy morphological segmentation of the corpus in a recursive
D10-1029 state-of-the-art unsupervised morphological segmentation is not yet practical for semantic
D10-1029 dictionary of the conventional morphological segmentations of words in the language . Although
D13-1004 induces syntactic categories and morphological segmentations by combining two well-known models
D08-1109 unsupervised multilingual learning to morphological segmentation ( Snyder and Barzilay , 2008
D10-1079 Our desired annotations include morphological segmentation , links to dictionary entries
C94-1036 iml ) lemented a system MSS ( Morphological Segmentation using Statistical information
C04-1152 character sequences for improve morphological segmentation , and do not consider syntactic
D13-1004 show a clear improvement in the morphological segmentations found by the joint model and
D12-1046 generative model was proposed for joint morphological segmentation and syntactic parsing for Hebrew
D09-1088 features are known up front . Morphological segmentation is also ambiguous , but for our
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