| other,1-1-E99-1023,ak | Dividing <term> sentences </term> in <term> chunks </term> of <term> words </term> is a useful <term> preprocessing step </term> for <term> parsing </term> , <term> information extraction </term> and <term> information retrieval </term> . | #30234 Dividingsentences in chunks of words is a useful preprocessing step for parsing, information extraction and information retrieval. | |
| other,3-1-E99-1023,ak | Dividing <term> sentences </term> in <term> chunks </term> of <term> words </term> is a useful <term> preprocessing step </term> for <term> parsing </term> , <term> information extraction </term> and <term> information retrieval </term> . | #30236 Dividing sentences inchunks of words is a useful preprocessing step for parsing, information extraction and information retrieval. | |
| other,5-1-E99-1023,ak | Dividing <term> sentences </term> in <term> chunks </term> of <term> words </term> is a useful <term> preprocessing step </term> for <term> parsing </term> , <term> information extraction </term> and <term> information retrieval </term> . | #30238 Dividing sentences in chunks ofwords is a useful preprocessing step for parsing, information extraction and information retrieval. | |
| tech,9-1-E99-1023,ak | Dividing <term> sentences </term> in <term> chunks </term> of <term> words </term> is a useful <term> preprocessing step </term> for <term> parsing </term> , <term> information extraction </term> and <term> information retrieval </term> . | #30242 Dividing sentences in chunks of words is a usefulpreprocessing step for parsing, information extraction and information retrieval. | |
| tech,12-1-E99-1023,ak | Dividing <term> sentences </term> in <term> chunks </term> of <term> words </term> is a useful <term> preprocessing step </term> for <term> parsing </term> , <term> information extraction </term> and <term> information retrieval </term> . | #30245 Dividing sentences in chunks of words is a useful preprocessing step forparsing, information extraction and information retrieval. | |
| tech,14-1-E99-1023,ak | Dividing <term> sentences </term> in <term> chunks </term> of <term> words </term> is a useful <term> preprocessing step </term> for <term> parsing </term> , <term> information extraction </term> and <term> information retrieval </term> . | #30247 Dividing sentences in chunks of words is a useful preprocessing step for parsing,information extraction and information retrieval. | |
| tech,17-1-E99-1023,ak | Dividing <term> sentences </term> in <term> chunks </term> of <term> words </term> is a useful <term> preprocessing step </term> for <term> parsing </term> , <term> information extraction </term> and <term> information retrieval </term> . | #30250 Dividing sentences in chunks of words is a useful preprocessing step for parsing, information extraction andinformation retrieval. | |
| tech,11-2-E99-1023,ak | ( Ramshaw and Marcus , 1995 ) have introduced a convenient <term> data representation </term> for <term> chunking </term> by converting it to a <term> tagging task </term> . | #30264 (Ramshaw and Marcus, 1995) have introduced a convenientdata representation for chunking by converting it to a tagging task. | |
| tech,14-2-E99-1023,ak | ( Ramshaw and Marcus , 1995 ) have introduced a convenient <term> data representation </term> for <term> chunking </term> by converting it to a <term> tagging task </term> . | #30267 (Ramshaw and Marcus, 1995) have introduced a convenient data representation forchunking by converting it to a tagging task. | |
| tech,20-2-E99-1023,ak | ( Ramshaw and Marcus , 1995 ) have introduced a convenient <term> data representation </term> for <term> chunking </term> by converting it to a <term> tagging task </term> . | #30273 (Ramshaw and Marcus, 1995) have introduced a convenient data representation for chunking by converting it to atagging task. | |
| tech,8-3-E99-1023,ak | In this paper we will examine seven different <term> data representations </term> for the <term> problem of recognizing noun phrase chunks </term> . | #30284 In this paper we will examine seven differentdata representations for the problem of recognizing noun phrase chunks. | |
| tech,12-3-E99-1023,ak | In this paper we will examine seven different <term> data representations </term> for the <term> problem of recognizing noun phrase chunks </term> . | #30288 In this paper we will examine seven different data representations for theproblem of recognizing noun phrase chunks. | |
| tech,6-4-E99-1023,ak | We will show that the the <term> data representation choice </term> has a minor influence on <term> chunking performance </term> . | #30301 We will show that the thedata representation choice has a minor influence on chunking performance. | |
| measure(ment),14-4-E99-1023,ak | We will show that the the <term> data representation choice </term> has a minor influence on <term> chunking performance </term> . | #30309 We will show that the the data representation choice has a minor influence onchunking performance. | |
| tech,7-5-E99-1023,ak | However , equipped with the most suitable <term> data representation </term> , our <term> memory-based learning chunker </term> was able to improve the best published <term> chunking results </term> for a <term> standard data set </term> . | #30319 However, equipped with the most suitabledata representation, our memory-based learning chunker was able to improve the best published chunking results for a standard data set. | |
| tech,11-5-E99-1023,ak | However , equipped with the most suitable <term> data representation </term> , our <term> memory-based learning chunker </term> was able to improve the best published <term> chunking results </term> for a <term> standard data set </term> . | #30323 However, equipped with the most suitable data representation, ourmemory-based learning chunker was able to improve the best published chunking results for a standard data set. | |
| other,21-5-E99-1023,ak | However , equipped with the most suitable <term> data representation </term> , our <term> memory-based learning chunker </term> was able to improve the best published <term> chunking results </term> for a <term> standard data set </term> . | #30333 However, equipped with the most suitable data representation, our memory-based learning chunker was able to improve the best publishedchunking results for a standard data set. | |
| other,25-5-E99-1023,ak | However , equipped with the most suitable <term> data representation </term> , our <term> memory-based learning chunker </term> was able to improve the best published <term> chunking results </term> for a <term> standard data set </term> . | #30337 However, equipped with the most suitable data representation, our memory-based learning chunker was able to improve the best published chunking results for astandard data set. |
