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COLLINS-PARSER

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最后更新: 2020-01-04 17:26:47

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所属分类多国语言处理
开发工具:Unix_Linux
文件大小:3879KB
下载次数:34
上传日期:2009-04-07 17:23:22
说明:  中心词驱动的短语结构句法分析器。该模型考虑了跟随介词短语的名词短语的中心词的作用。 有MIT大学Colling开发,是目前国际上工人的最好的英语句法分析器
(Head-driven Phrase Structure Parser. The model considered the prepositional phrase following the noun phrase the central role of the word. MIT has developed the University of Colling, workers are on the current international best English Parser)

文件列表
COLLINS-PARSER
..............\code
..............\....\chart.c
..............\....\chart.h
..............\....\edges.c
..............\....\edges.h
..............\....\effhash.c
..............\....\effhash.h
..............\....\genprob.c
..............\....\genprob.h
..............\....\GNU_GENERAL_PUBLIC_LICENSE
..............\....\grammar.c
..............\....\grammar.h
..............\....\hash.c
..............\....\hash.h
..............\....\key.c
..............\....\key.h
..............\....\lexicon.c
..............\....\lexicon.h
..............\....\main.c
..............\....\Makefile
..............\....\mymalloc.c
..............\....\mymalloc.h
..............\....\mymalloc_char.c
..............\....\mymalloc_char.h
..............\....\parser
..............\....\prob.c
..............\....\prob.h
..............\....\prob_witheffhash.c
..............\....\prob_witheffhash.h
..............\....\readevents.c
..............\....\readevents.h
..............\....\sentence.c
..............\....\sentence.h
..............\collins99.thesis.ps
..............\examples
..............\........\sec00.tagged
..............\........\sec23.tagged
..............\GNU_GENERAL_PUBLIC_LICENSE
..............\README
..............\sec23
..............\.....\cleanSec23.pl
..............\.....\merge.prl
..............\.....\proc_pout.prl
..............\.....\README.sec23
..............\.....\sec23.model1
..............\.....\sec23.model1.final
..............\.....\sec23.model1.scores
..............\.....\sec23.model2
..............\.....\sec23.model2.final
..............\.....\sec23.model2.merged
..............\.....\sec23.model2.scores
..............\.....\sec23.model3
..............\.....\sec23.model3.final
..............\.....\sec23.model3.merged
..............\.....\sec23.model3.scores
..............\.....\sec23.tgrep.clean

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