model-def.properties

#Definitions to load the model

#All possible annotations:
## "tokenize",  "cleanxml",  "ssplit",  "pos",  "lemma",  "ner",  "regexner",  "tokensregex",  "entitymentions",  "gender", 
## "truecase",  "parse",  "dcoref",  "coref",  "coref.mention",  "relation",  "sentiment",  "cdc",  "depparse",  "natlog", 
## "openie",  "quote",  "quote.attribution",  "udfeats",  "entitylink",  "kbp"

annotators = tokenize, ssplit, pos, lemma, ner, depparse

######model = edu/stanford/nlp/models/parser/nndep/english_UD.gz
#####tagger = edu/stanford/nlp/models/pos-tagger/english-left3words/english-left3words-distsim.tagger


# tokenize
tokenize.language = es

# The first model uses a coarser version of Ancora tags (with less features marked).
# It is the correct version to use with our PCFG or SR parsers
#pos.model = edu/stanford/nlp/models/pos-tagger/spanish/spanish-distsim.tagger
pos.model = edu/stanford/nlp/models/pos-tagger/spanish/spanish-ud.tagger
# The below part of speech tagger is the correct one to use with the dependency parser
# pos.model = edu/stanford/nlp/models/pos-tagger/spanish/spanish-ud.tagger

# ner
ner.model = edu/stanford/nlp/models/ner/spanish.ancora.distsim.s512.crf.ser.gz
ner.applyNumericClassifiers = true
ner.useSUTime = true
ner.language = es

# sutime
sutime.language = spanish

# parse
parse.model = edu/stanford/nlp/models/lexparser/spanishPCFG.ser.gz
# parse.model = edu/stanford/nlp/models/srparser/spanishSR.ser.gz

# depparse
depparse.model = edu/stanford/nlp/models/parser/nndep/UD_Spanish.gz
depparse.language = spanish

# regexner
ner.fine.regexner.mapping = edu/stanford/nlp/models/kbp/spanish/kbp_regexner_mapping_sp.tag
ner.fine.regexner.validpospattern = ^(NOUN|ADJ|PROPN).*
ner.fine.regexner.ignorecase = true
ner.fine.regexner.noDefaultOverwriteLabels = CITY,COUNTRY,STATE_OR_PROVINCE

# kbp
kbp.semgrex = edu/stanford/nlp/models/kbp/spanish/semgrex
kbp.tokensregex = edu/stanford/nlp/models/kbp/spanish/tokensregex
kbp.model = none
kbp.language = es

# entitylink
entitylink.caseless = true
entitylink.wikidict = edu/stanford/nlp/models/kbp/spanish/wikidict_spanish.tsv