#-------------------------------------------------------------------
#-----------   D E P R E C A T E D !! ------------------------------
#----------- this is not used anymore and kept temporarily ---------
#----------- for compatibility with older GROBID versions ----------
#-------------------------------------------------------------------
#-------------------------------------------------------------------


#-------------------- resource directories ---------------------
# properties of where to find directories necessary for GROBID
# EACH KEY REFERENCING A PATH HAS TO ENDS WITH ".path"
grobid.temp.path=./tmp

#-------------------- external/native libs ---------------------
#path to folder containing native libraries of 3rd parties
grobid.nativelibrary.path=./lib
grobid.3rdparty.pdf2xml.path=./pdf2xml
grobid.3rdparty.pdf2xml.memory.limit.mb=6096
grobid.3rdparty.pdf2xml.timeout.sec=60

#-------------------- consolidation --------------------
# Define the bibliographical data consolidation service to be used, either "crossref" for CrossRef REST API or "glutton" for https://github.com/kermitt2/biblio-glutton
grobid.consolidation.service=crossref
#grobid.consolidation.service=glutton
#org.grobid.glutton.host=cloud.science-miner.com/glutton
#org.grobid.glutton.port=0
org.grobid.glutton.host=localhost
org.grobid.glutton.port=8080
#org.grobid.crossref.mailto=toto@titi.tutu
#org.grobid.crossref.token=yourmysteriouscrossrefmetadataplusauthorizationtokentobeputhere

#-------------------- proxy --------------------
#proxy to be used for external call to the crossref REST API service or Glutton service if not deployed under proxy ("null" when no proxy)
grobid.proxy_host=null
grobid.proxy_port=null

#-------------------- models ------------------
grobid.crf.engine=wapiti
#grobid.crf.engine=delft
#grobid.crf.engine=crfpp

# wapiti must be used for the fulltext and segmentation models because they
# are not covered by DeLFT for the moment (too long sequences for the deep 
# learning models). header and reference_segmenter deep learning models might 
# also be difficult to use without enough available memory (GPU or CPU).
grobid.crf.engine.segmentation=wapiti
grobid.crf.engine.fulltext=wapiti

# replace here hyphen in model name by underscore, e.g. name-citation -> name_citation
#grobid.crf.engine.reference_segmenter=wapiti
#grobid.crf.engine.name_header=wapiti
#grobid.crf.engine.header=wapiti
#grobid.crf.engine.date=wapiti
#grobid.crf.engine.figure=wapiti
#grobid.crf.engine.table=wapiti
#grobid.crf.engine.name_citation=wapiti
#grobid.crf.engine.affiliation_address=delft
#grobid.crf.engine.citation=delft

grobid.delft.useELMo=false

grobid.delft.install=../delft
grobid.delft.python.virtualEnv=
grobid.delft.architecture=BidLSTM_CRF_FEATURES
#grobid.delft.architecture=scibert

#-------------------- runtime ------------------
grobid.pdf.blocks.max=100000
grobid.pdf.tokens.max=1000000

#-------------------- training ------------------
#number of threads for training the wapiti models (0 to use all available processors)
grobid.nb_threads=0

#-------------------- language processing bazaar  ------------------

# actual implementation of language recognition to be used
grobid.language_detector_factory=org.grobid.core.lang.impl.CybozuLanguageDetectorFactory

# actual implementation of sentence segmentation to be used
grobid.sentence_detector_factory=org.grobid.core.lang.impl.OpenNLPSentenceDetectorFactory
#grobid.sentence_detector_factory=org.grobid.core.lang.impl.PragmaticSentenceDetectorFactory

#-------------------- pooling -------------------
# Maximum parallel connections allowed
org.grobid.max.connections=10
# Maximum time wait to get a connection when the pool is full (in seconds)
org.grobid.pool.max.wait=1