import sys
import config_data
sys.path.append(config_data.jarvis_folder_location)
from JarvisN.database.datahelper import DataDbHelper
td = []
dbh = DataDbHelper()
result = dbh.getResult(
"SELECT sentence, label2 FROM trainingdata WHERE label1='dictionary'")
dbh.closeConnection()
for row in result:
td.append((row[0], row[1]))
print(td)
from nltk.tokenize import word_tokenize
from nltk.classify.scikitlearn import SklearnClassifier
from sklearn.naive_bayes import MultinomialNB, BernoulliNB
from sklearn.linear_model import LogisticRegression, SGDClassifier
from sklearn.svm import SVC, LinearSVC, NuSVC
import sys
import os
sys.path.append(r"C:\Users\Dhaval\Documents\GitHub"
) # Your JarvisN folder Location... Replace it
from JarvisN.database.datahelper import DataDbHelper # Rename folder to JarvisN not JarvisN-Master
#td = []
dbh = DataDbHelper()
#result = dbh.getResult("SELECT sentence, label1 FROM trainingdata") # execute ur query here
result = dbh.getResult(
"SELECT sentence, entitys, entitye, entity FROM trainingdata WHERE label1='music'"
) # execute ur query here
dbh.closeConnection()
file = open('nerData.tsv', 'w')
for row in result:
sentence = row[0].split(" ")
start = row[1]
end = row[2]
if row[3] == 'none':
continue
print(start, end)
i = 0
for word in sentence:
if i >= start and i < end:
file.write(word + "\t" + row[3])
#if (end - start) == 1: