nlp_ie_23.py

# rule 1 modified function
def rule1_mod(text):
    
    doc = nlp(text)
    
    sent = []
    
    for token in doc:
        # root word
        if (token.pos_=='VERB'):
            
            phrase =''
            
            # only extract noun or pronoun subjects
            for sub_tok in token.lefts:
                
                if (sub_tok.dep_ in ['nsubj','nsubjpass']) and (sub_tok.pos_ in ['NOUN','PROPN','PRON']):
                    
                    # look for subject modifier
                    adj = rule2_mod(text,sub_tok.i)
                    
                    phrase += adj + ' ' + sub_tok.text

                    # save the root word of the word
                    phrase += ' '+token.lemma_ 

                    # check for noun or pronoun direct objects
                    for sub_tok in token.rights:
                        
                        if (sub_tok.dep_ in ['dobj']) and (sub_tok.pos_ in ['NOUN','PROPN']):
                            
                            # look for object modifier
                            adj = rule2_mod(text,sub_tok.i)
                            
                            phrase += adj+' '+sub_tok.text
                            sent.append(phrase)
            
    return sent