==============================Run CoreNLP======================================= 



input file:  /home/egaytan/automatic-extraction-growth-conditions/CoreNLP/input/annotation/bg_sentences_v4.txt

output directory:  /home/egaytan/automatic-extraction-growth-conditions/CoreNLP/output/annotation

regex file:  /home/egaytan/automatic-extraction-growth-conditions/CoreNLP/input/NER/inputEntities.txt

java -mx5g -cp "/usr/local/stanford-corenlp-full-2018-10-05/*" edu.stanford.nlp.pipeline.StanfordCoreNLP -annotators tokenize,ssplit,pos,lemma,regexner -outputFormat conll -file /home/egaytan/automatic-extraction-growth-conditions/CoreNLP/input/annotation/bg_sentences_v4.txt -outputDirectory /home/egaytan/automatic-extraction-growth-conditions/CoreNLP/output/annotation -regexner.mapping /home/egaytan/automatic-extraction-growth-conditions/CoreNLP/input/NER/inputEntities.txt -outputExtension .ner
[main] INFO edu.stanford.nlp.pipeline.StanfordCoreNLP - Adding annotator tokenize
[main] INFO edu.stanford.nlp.pipeline.StanfordCoreNLP - Adding annotator ssplit
[main] INFO edu.stanford.nlp.pipeline.StanfordCoreNLP - Adding annotator pos
[main] INFO edu.stanford.nlp.tagger.maxent.MaxentTagger - Loading POS tagger from edu/stanford/nlp/models/pos-tagger/english-left3words/english-left3words-distsim.tagger ... done [0.6 sec].
[main] INFO edu.stanford.nlp.pipeline.StanfordCoreNLP - Adding annotator lemma
[main] INFO edu.stanford.nlp.pipeline.StanfordCoreNLP - Adding annotator regexner
[main] INFO edu.stanford.nlp.pipeline.TokensRegexNERAnnotator - regexner: Read 9253 unique entries out of 13838 from /home/egaytan/automatic-extraction-growth-conditions/CoreNLP/input/NER/inputEntities.txt, 0 TokensRegex patterns.

Processing file /home/egaytan/automatic-extraction-growth-conditions/CoreNLP/input/annotation/bg_sentences_v4.txt ... writing to /home/egaytan/automatic-extraction-growth-conditions/CoreNLP/output/annotation/bg_sentences_v4.txt.ner
Untokenizable:  (U+F06D, decimal: 61549)
Annotating file /home/egaytan/automatic-extraction-growth-conditions/CoreNLP/input/annotation/bg_sentences_v4.txt ... done [236.1 sec].

Annotation pipeline timing information:
TokenizerAnnotator: 2.2 sec.
WordsToSentencesAnnotator: 4.3 sec.
POSTaggerAnnotator: 214.7 sec.
MorphaAnnotator: 5.6 sec.
TokensRegexNERAnnotator: 9.3 sec.
TOTAL: 236.1 sec. for 2373062 tokens at 10051.1 tokens/sec.
Pipeline setup: 0.9 sec.
Total time for StanfordCoreNLP pipeline: 239.0 sec.