34 lines
1.6 KiB
Properties
34 lines
1.6 KiB
Properties
annotators = tokenize, ssplit, pos, lemma, ner, depparse, coref, kbp
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tokenize.language = en
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# Some other annotators are also available for English and can be optionally loaded, e.g.:
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# annotators = tokenize, ssplit, pos, lemma, truecase
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# This is an example of the "full" pipeline, though there are even more annotators than this:
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# annotators = tokenize,cleanxml,ssplit,pos,lemma,ner,parse,depparse,coref,natlog,openie,kbp,entitylink,sentiment,quote
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# Options like the ones below are being set as defaults in code
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# pos.model = edu/stanford/nlp/models/pos-tagger/english-left3words-distsim.tagger
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# ner.model = edu/stanford/nlp/models/ner/english.all.3class.distsim.crf.ser.gz,\
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# edu/stanford/nlp/models/ner/english.muc.7class.distsim.crf.ser.gz,\
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# edu/stanford/nlp/models/ner/english.conll.4class.distsim.crf.ser.gz
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# sutime.rules = edu/stanford/nlp/models/sutime/defs.sutime.txt,edu/stanford/nlp/models/sutime/english.sutime.txt,\
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# edu/stanford/nlp/models/sutime/english.holidays.sutime.txt
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# ner.fine.regexner.mapping =
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# "ignorecase=true,validpospattern=(NN|JJ|ADD).*,edu/stanford/nlp/models/kbp/english/gazetteers/regexner_caseless.tab;\
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# edu/stanford/nlp/models/kbp/english/gazetteers/regexner_cased.tab"
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# ner.fine.regexner.noDefaultOverwriteLabels = CITY
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# parse.model = edu/stanford/nlp/models/lexparser/englishPCFG.ser.gz
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# depparse.model = edu/stanford/nlp/models/parser/nndep/english_UD.gz
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# coref.algorithm = statistical
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# coref.md.type = dependency
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# coref.statistical.rankingModel = edu/stanford/nlp/models/coref/statistical/ranking_model.ser.gz
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