# Part of Speach (POS) Based Entity Extraction
# Aimed at Extracting Relationships

class PosExtractor(object):

    def __init__(self, debug = False):
        pass
        
    # Generator to return tokenized sentences
    def extract_entities(self, token_sent):
        return True

# Part of Speach (POS) Based Entity Extraction
# Aimed at Extracting Relationships

class PosExtractor(object):

    def __init__(self, debug = False):
        pass
        
    # Generator to return tokenized sentences
    def extract_entities(self, token_sent):
        # Use regex matching to identify relational phrases
        # VP?
        # V(W*P)?
        # 
        # V1: 'RB'
        # V2: 'MD', 'VB', 'VBD', 'VBP', 'VBZ', 'VBG', 'VBN'
        # V3: 'RP', 'RB'
        # (V1)? + (V2) + (V3)?
        #
        # P1: 'RB'
        # P2: 'IN', 'TO', 'RP'
        # P3: 'RB'
        # (P1)? + (P2) + (P3)?
        #
        # W: 'PRP$', 'CD', 'DT', 'JJ', 'JJS', 'JJR', 'NN', 'NNS', 'NNP', 'NNPS', 'POS', 'RB', 'RBR', 'RBS', 'VBN', 'VBG'
        # (W1)
        #
        
        
        
        
        return True

update extractor with basic pos pattern