A00-2035 not is absolutely crucial for sentence splitting . Unfortunately , abbreviations
A00-2035 the local context of potential sentence splitting punctu - ation . However , what
D11-1038 and apposition . An example of a sentence splitting rule is illustrated in Figure
A00-2035 which follows the period or other sentence splitting punctuation . In general , when
D11-1038 commonest simplification operations is sentence splitting which usually produces longer
C04-1017 system is equipped with another sentence splitting method based on parsing trees
D11-1038 and rules ( 4 ) -- ( 6 ) involve sentence splitting . Examples of common lexical
C04-1017 well . In order to supplement sentence splitting based on word-sequence characteristics
A00-1012 another problem sometimes called " sentence splitting " . This problem aims to identify
D15-1063 linguistic preprocessing steps are sentence splitting and tokenization . Thus , we
A00-2035 Aberdeen et al. , 1995 ) contains a sentence splitting module which employs over 100
C02-1027 filtered by special constraints . The sentence splitting and tokenising rules were adapted
C04-1017 method , we generate candidates for sentence splitting based on N-grams , and select
C02-1027 pre-processing modules for tokenisation , sentence splitting , paragraph segmentation , partof-speech
A00-2035 improvement in the performance on sentence splitting and about a 40 % improvement
C02-1027 includes modules for POS tag - ging , sentence splitting , clause segmentation , parsing
A00-2035 reducing the ambiguity for the sentence splitting module . The second row of Table
A00-2035 achieved a 0.65 % error rate on sentence splitting on the Brown Corpus and 1.39
D15-1157 errors that result from noisy sentence splitting and tokenisation that must be
D15-1148 separately model the need for sentence splitting ( Zhu et al. , 2010 ; Woodsend
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