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#
# Copyright (c) 2013-present, Anoop Kunchukuttan
# All rights reserved.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
#
#Program for sentence splitting of Indian language input
#
# @author Anoop Kunchukuttan
#
"""
Sentence splitter for Indian languages. Contains a rule-based
sentence splitter that can understand common non-breaking phrases
in many Indian languages.
"""
import re
from indicnlp.transliterate import unicode_transliterate
DELIM_PAT=re.compile(r'[\.\?!\u0964\u0965]')
def is_acronym_abbvr(text,lang):
"""Is the text a non-breaking phrase
Args:
text (str): text to check for non-breaking phrase
lang (str): ISO 639-2 language code
Returns:
boolean: true if `text` is a non-breaking phrase
"""
ack_chars = {
## acronym for latin characters
'ए', 'ऎ',
'बी', 'बि',
'सी', 'सि',
'डी', 'डि',
'ई', 'इ',
'एफ', 'ऎफ',
'जी', 'जि',
'एच','ऎच',
'आई', 'आइ','ऐ',
'जे', 'जॆ',
'के', 'कॆ',
'एल', 'ऎल',
'एम','ऎम',
'एन','ऎन',
'ओ', 'ऒ',
'पी', 'पि',
'क्यू', 'क्यु',
'आर',
'एस','ऎस',
'टी', 'टि',
'यू', 'यु',
'वी', 'वि', 'व्ही', 'व्हि',
'डब्ल्यू', 'डब्ल्यु',
'एक्स','ऎक्स',
'वाय',
'जेड', 'ज़ेड',
## add halant to the previous English character mappings.
'एफ्',
'ऎफ्',
'एच्',
'ऎच्',
'एल्',
'ऎल्',
'एम्',
'ऎम्',
'एन्',
'ऎन्',
'आर्',
'एस्',
'ऎस्',
'एक्स्',
'ऎक्स्',
'वाय्',
'जेड्', 'ज़ेड्',
#Indic vowels
'ऄ',
'अ',
'आ',
'इ',
'ई',
'उ',
'ऊ',
'ऋ',
'ऌ',
'ऍ',
'ऎ',
'ए',
'ऐ',
'ऑ',
'ऒ',
'ओ',
'औ',
'ॠ',
'ॡ',
#Indic consonants
'क',
'ख',
'ग',
'घ',
'ङ',
'च',
'छ',
'ज',
'झ',
'ञ',
'ट',
'ठ',
'ड',
'ढ',
'ण',
'त',
'थ',
'द',
'ध',
'न',
'ऩ',
'प',
'फ',
'ब',
'भ',
'म',
'य',
'र',
'ऱ',
'ल',
'ळ',
'ऴ',
'व',
'श',
'ष',
'स',
'ह',
## abbreviation
'श्री',
'डॉ',
'कु',
'चि',
'सौ',
}
return unicode_transliterate.UnicodeIndicTransliterator.transliterate(text,lang,'hi') in ack_chars
def sentence_split(text,lang,delim_pat=DELIM_PAT): ## New signature
"""split the text into sentences
A rule-based sentence splitter for Indian languages written in
Brahmi-derived scripts. The text is split at sentence delimiter
boundaries. The delimiters can be configured by passing appropriate
parameters.
The sentence splitter can identify non-breaking phrases like
single letter, common abbreviations/honorofics for some Indian
languages.
Args:
text (str): text to split into sentence
lang (str): ISO 639-2 language code
delim_pat (str): regular expression to identify sentence delimiter characters
Returns:
list: list of sentences identified from the input text
"""
line = text
### Phase 1: break on sentence delimiters.
cand_sentences=[]
begin=0
text = text.strip()
for mo in delim_pat.finditer(text):
p1=mo.start()
p2=mo.end()
## NEW
if p1>0 and text[p1-1].isnumeric():
continue
end=p1+1
s= text[begin:end].strip()
if len(s)>0:
cand_sentences.append(s)
begin=p1+1
s= text[begin:].strip()
if len(s)>0:
cand_sentences.append(s)
# print(cand_sentences)
# print('====')
# return cand_sentences
### Phase 2: Address the fact that '.' may not always be a sentence delimiter
### Method: If there is a run of lines containing only a word (optionally) and '.',
### merge these lines as well one sentence preceding and succeeding this run of lines.
final_sentences=[]
sen_buffer=''
bad_state=False
for i, sentence in enumerate(cand_sentences):
words=sentence.split(' ')
#if len(words)<=2 and words[-1]=='.':
if len(words)==1 and sentence[-1]=='.':
bad_state=True
sen_buffer = sen_buffer + ' ' + sentence
## NEW condition
elif sentence[-1]=='.' and is_acronym_abbvr(words[-1][:-1],lang):
if len(sen_buffer)>0 and not bad_state:
final_sentences.append(sen_buffer)
bad_state=True
sen_buffer = sentence
elif bad_state:
sen_buffer = sen_buffer + ' ' + sentence
if len(sen_buffer)>0:
final_sentences.append(sen_buffer)
sen_buffer=''
bad_state=False
else: ## good state
if len(sen_buffer)>0:
final_sentences.append(sen_buffer)
sen_buffer=sentence
bad_state=False
if len(sen_buffer)>0:
final_sentences.append(sen_buffer)
return final_sentences
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