TopicModelingForSummarization / src /nltk_utilities.py
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### Imports
import nltk
from nltk.tokenize import sent_tokenize
nltk.data.path.append("/nltk_data/")
class NltkSegmentizer:
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"""
Definition of attributes
"""
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"""
Function: __init__
"""
def __init__(self):
print("Initializing NltkSegmentizer object")
nltk.download('punkt')
##==========================================================================================================
"""
Function: segment_into_sentences
"""
def segment_into_sentences(self, src_text="", _format=""):
intermediate_result = None
if isinstance(src_text, str):
intermediate_result = sent_tokenize(src_text)
elif isinstance(src_text, list):
intermediate_result = list()
for sent in src_text:
intermediate_result.extend(sent_tokenize(sent))
return intermediate_result
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