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import spacy | |
# Load the English language model | |
nlp = spacy.load("en_core_web_sm") | |
# Define a list of obligation words | |
obligation_words = ["must", "will", "use", "may", "provides", 'is obliged to', | |
'has to', 'needs to', 'is required to', | |
"shall", "should", "ought to", "required", "obligated", "duty"] | |
def extract_keyphrase(text): | |
# Parse the input text with SpaCy | |
doc = nlp(text) | |
# Initialize a list to store sentences with obligation words | |
obligation_sentences = [] | |
# Iterate through the sentences in the document | |
for sentence in doc.sents: | |
# Check if any of the obligation words appear in the sentence | |
if any(word.text.lower() in obligation_words for word in sentence): | |
obligation_sentences.append(sentence.text) | |
return obligation_sentences | |