(input_text, caseless=False)
return tagged
Get pos tagged and ner from the CoreNLP Server

    :param input_text: input text as a string
    :return: tokenized text with pos and ne tags
    >>> get_tagged_from_server("Light explodes over Pep Guardiola's head in Bernabeu press room. Will Mourinho stop at nothing?! Heh heh")[0] == \
    {'characterOffsetBegin': 0, 'ner': 'O', 'pos': 'JJ', 'characterOffsetEnd': 5, 'originalText': 'Light', 'lemma': 'light'}
    True
Get pos tagged and ner from the CoreNLP Server
Get pos tagged and ner from the CoreNLP Server
def get_tagged_from_server(input_text, caseless=False):
    """
    Get pos tagged and ner from the CoreNLP Server

    :param input_text: input text as a string
    :return: tokenized text with pos and ne tags
    >>> get_tagged_from_server("Light explodes over Pep Guardiola's head in Bernabeu press room. Will Mourinho stop at nothing?! Heh heh")[0] == \
    {'characterOffsetBegin': 0, 'ner': 'O', 'pos': 'JJ', 'characterOffsetEnd': 5, 'originalText': 'Light', 'lemma': 'light'}
    True
    """
    if len(input_text.strip()) == 0:
        return []
    if "@" in input_text or "#" in input_text:
        input_text = _preprocess_twitter_handles(input_text)
    input_text = remove_links(input_text)
    input_text = _preprocess_corenlp_input(input_text)
    if caseless:
        input_text = input_text.lower()
    corenlp_output = corenlp.annotate(input_text,
                                      properties={**corenlp_properties, **corenlp_caseless} if caseless else corenlp_properties
                                      ).get("sentences", [])
    tagged = [{k: t[k] for k in {"index", "originalText", "pos", "ner", "lemma", "characterOffsetBegin", "characterOffsetEnd"}}
              for sent in corenlp_output for t in sent['tokens']]
    return tagged
def get_tagged_from_server ( input_text , caseless = False ) : if len ( input_text . strip ( ) ) == 0 : return [ ] if "@" in input_text or "#" in input_text : input_text = _preprocess_twitter_handles ( input_text ) input_text = remove_links ( input_text ) input_text = _preprocess_corenlp_input ( input_text ) if caseless : input_text = input_text . lower ( ) corenlp_output = corenlp . annotate ( input_text , properties = { * * corenlp_properties , * * corenlp_caseless } if caseless else corenlp_properties ) . get ( "sentences" , [ ] ) tagged = [ { k : t [ k ] for k in { "index" , "originalText" , "pos" , "ner" , "lemma" , "characterOffsetBegin" , "characterOffsetEnd" } } for sent in corenlp_output for t in sent [ 'tokens' ] ] return tagged