amService_Nlp.py

import spacy

# Load spaCy model
nlp = spacy.load("en_core_web_md")
# nlp = spacy.load('en_core_web_sm') # Consider using small model

ner_ban_list = [
    "PERCENT",
    "MONEY",
    "QUANTITY",
    "ORDINAL",
    "CARDINAL",
    "DATE"
]

###### Call spaCy and get Named Entities as keywords ######
###### This ignores some NERs which are specified    ######
###### in the hardcoded list above                   ######
def ner_caller(article_in):
    # Process the text with spaCy
    return_list = []
    doc = nlp(article_in)
    for ent in doc.ents:
        # print(ent.text, ent.start_char, ent.end_char, ent.label_)
        if ent.label_ not in ner_ban_list and ent.text not in return_list:
            return_list.append(ent.text)
    return return_list # returns empty list if nothing found


               
## Testing             
# x = ner_caller("""When Sebastian Thrun started working on self-driving cars at Google in 2007,
#     few people outside of the company took him seriously. “I can tell you very senior 
#     CEOs of major American car companies would shake my hand and turn away because I 
#     wasn’t worth talking to,” said Thrun, now the co-founder and CEO of online higher 
#     education startup Udacity, in an interview with Recode earlier this week.

#     The Mona Lisa and the Statue of David were on display in the MOMA New York.

#     COVID-19 is a devastating virus currently ravaging the world.
    
#     A little less than a decade later, dozens of self-driving startups have cropped up 
#     while automakers around the world clamor, wallet in hand, to secure their place in 
#     the fast-moving world of fully automated transportation.""")
# print(x)